BlueHippo is seeking a highly driven and resourceful Placement Consultant to lead the end-to-end placement of Instructional Designers and candidates with teaching degrees across the United States. This is a focused, short-term, results-oriented engagement designed to quickly match high-caliber instructional design talent with the right clients across the U.S. and South America.

The ideal candidate will work directly with consultants on our bench, scan multiple job boards daily, craft tailored cover letters using AI tools such as ChatGPT, manage submissions, coordinate interviews, and successfully place candidates. This role demands persistence, AI-fluency, exceptional written communication, and the ability to deliver measurable placements within tight timelines.

Key Responsibilities:

• Candidate Management: Work directly with Instructional Designer consultants and candidates with teaching degrees to understand their experience, strengths, target roles, and availability.
• Job Market Scanning: Continuously scan and monitor multiple job boards and platforms daily, including but not limited to:
• LinkedIn, Indeed, Dice, Monster, ZipRecruiter, Glassdoor
• SimplyHired, CareerBuilder, FlexJobs, Remote.co, We Work Remotely
• Higher-ed and L&D-specific boards (HigherEdJobs, ATD Job Bank, eLearning Industry, InsideHigherEd)
• Client career pages and staffing partner portals
• AI-Driven Outreach: Use ChatGPT and other AI tools to draft highly customized cover letters, resume tweaks, and recruiter outreach messages tailored to each role.
• Application Submissions: Submit candidate profiles to relevant openings across U.S. and South American clients, tracking every submission in a centralized tracker.
• Interview Coordination: Schedule, prep, and coach candidates through phone screens, technical/instructional interviews, portfolio reviews, and final rounds.
• Client Relationships: Liaise with hiring managers, vendor managers, and staffing partners to push candidate profiles, negotiate rates, and close placements.
• Daily Reporting: Provide a structured daily update to BlueHippo leadership covering:
• Number of new roles identified
• Applications submitted (with role, client, location)
• Interviews scheduled / completed
• Offers / placements in progress
• Blockers and next-day plan
• Pipeline Building: Maintain a healthy pipeline of active opportunities for each consultant; ensure no consultant goes more than 24–48 hours without new submissions.
• Negotiation & Onboarding Support: Support offer negotiation, rate discussions, paperwork, and smooth onboarding of placed candidates.
• Compliance: Ensure all submissions and placements comply with client requirements, work authorization rules, and BlueHippo internal policies.

Qualifications:

• 2+ years of experience in recruiting, staffing, or placement consulting, preferably placing Instructional Designers, L&D professionals, eLearning specialists, curriculum developers, or candidates with teaching/education degrees.
• Demonstrated track record of successful placements in the U.S. market (South American client experience is a strong plus).
• Strong understanding of Instructional Design roles, frameworks (ADDIE, SAM), and tools (Articulate Storyline, Captivate, Rise 360, Camtasia, LMS platforms).
• AI-fluent: Hands-on experience using ChatGPT (or similar tools) to write cover letters, customize resumes, and accelerate recruiting workflows.
• Excellent written and verbal English communication; ability to write compelling, client-ready cover letters.
• Highly organized — comfortable managing multiple consultants, submissions, and pipelines simultaneously with detailed daily tracking.
• Self-starter who thrives in a fast-paced, target-driven, remote environment.
• Familiarity with ATS / CRM tools, Google Workspace, and basic spreadsheet tracking.
• Comfortable working across U.S. time zones, with flexibility for occasional South American client calls.

Nice to Have:

• Existing network of U.S. hiring managers, vendor managers, or staffing partners in L&D / Instructional Design.
• Spanish or Portuguese language skills (for South American client engagement).
• Experience working with bench sales / consultant placement models.

Engagement Terms:

• Duration: 60 days (short-term contract)
• Base Compensation: INR 50,000 for the 60-day engagement
• Placement Bonus: INR 10,000 per successful placement (uncapped)
• Conversion: Strong performers will be offered a full-time role at BlueHippo at the end of the 60-day engagement.
• Start Date: ASAP
• Work Setup: Fully remote

Performance Expectations (60-Day Engagement):

• Submit candidate profiles to qualified roles daily, with measurable submission targets.
• Generate consistent interview activity within the first 2 weeks.
• Deliver at least one successful placement within the first 30 days, with multiple placements expected over the 60-day period.
• Maintain transparent, detailed daily reporting throughout the engagement.

Why Join BlueHippo?
BlueHippo is building a high-performance placement engine focused on quality, speed, and consultant success. This role offers high earning potential through placement bonuses, direct visibility with leadership, and a clear path to a full-time role for top performers. If you love the thrill of closing placements, working with great talent, and using AI to outpace traditional recruiting, we want to hear from you.

We are looking for an experienced Senior Salesforce Developer to design, develop, and implement customized solutions within the Salesforce platform. The ideal candidate will have strong expertise in Salesforce development, integration, and deployment, along with the ability to lead technical initiatives and mentor team members.

Key Responsibilities

• Design and develop scalable Salesforce solutions using Apex, Lightning Web Components (LWC), Visualforce, and Salesforce APIs.
• Customize Salesforce applications to support business requirements and improve user experience.
• Lead end-to-end development activities including requirement analysis, coding, testing, deployment, and support.

We are looking for a hands-on MuleSoft Architect / Developer to design, build, and deliver MuleSoft-based ETL integrations for a US-based client. The core scope is to extract data from Oracle databases and SFTP file feeds, transform it in Mule, and load it into Salesforce — targeting the Account, Order, and Order Line Item (OLI) standard objects.

This is a pure MuleSoft role — Salesforce is the destination system, not a Salesforce development engagement. The candidate will not be writing Apex, building Lightning components, or performing Salesforce administration. The work is owning the integration end-to-end on the MuleSoft side: source-to-target mapping, DataWeave transformations, Salesforce Connector usage, error handling, reconciliation, and performance.

The role is a hybrid Architect + Developer position — the right candidate will own both the integration design and the hands-on build. This role offers flexibility to work as a part-time, contract, or full-time team member, depending on availability and preferences.

Engagement Details:

• Initial Duration: 2 months, with strong potential to extend through end of the calendar year based on performance and project needs.
• Work Mode: Remote, with mandatory US EST overlap until 1:00 PM EST daily (≈ until 10:30 PM IST).
• Client: US-based.
• Compensation – Initial 2 Months: INR 3,00,000 (3 Lakhs) total, paid as a single lump sum upon successful completion of the 2-month engagement (no advance / no milestone payments).

Key Responsibilities:

• Architect and hands-on develop MuleSoft (Mule 4) integration flows that load data from Oracle (JDBC) and SFTP file feeds (CSV, fixed-width, XML, JSON) into Salesforce.
• Map and load data into the Salesforce Account, Order, and Order Line Item (OLI) standard objects, maintaining parent-child relationships.
• Use the MuleSoft Salesforce Connector with Bulk API v1 / v2, upsert by External ID, and composite/tree requests for parent-child loads.
• Build performant, idempotent ETL pipelines with watermarking / incremental loads from Oracle and reliable file-handling patterns for SFTP.
• Develop clean DataWeave 2.0 transformations including complex mappings, lookups, aggregations, and type coercion.
• Implement robust error handling, retries, dead-letter routing, logging, monitoring, alerting, and reconciliation outputs.
• Tune performance for high-volume Salesforce loads while staying within Salesforce API and governor limits.
• Deploy Mule applications to CloudHub or Runtime Fabric, and set up CI/CD using Maven, Git, and Jenkins / GitHub Actions / Azure DevOps.
• Write MUnit test cases and ensure code quality.
• Participate in daily standups and design discussions with the US client during EST hours.
• Produce technical documentation, source-to-target mappings, runbooks, and handover artifacts.

Required Skills & Qualifications:

• Bachelor's degree in Computer Science, Engineering, or a related field.
• Minimum 6 years of overall IT experience with strong hands-on MuleSoft Anypoint Platform (Mule 4) experience.
• Proven hands-on experience with the MuleSoft Salesforce Connector, including Bulk API v1 / v2, upsert by External ID, and loading parent-child object hierarchies (Account → Order → OLI).
• Strong knowledge of the Salesforce data model from an integration perspective — Account, Order, OLI, Pricebook references, standard vs. custom fields. (No Apex / Lightning development required.)
• Hands-on with the MuleSoft Database Connector / JDBC against Oracle — performant SQL extracts, incremental / CDC patterns.
• Hands-on with the MuleSoft SFTP Connector — scheduled pickups, archival, file locking, large-file handling.
• Strong DataWeave 2.0 skills — complex mappings, lookups, aggregations, type coercion.
• Experience with CloudHub / Runtime Fabric deployments and CI/CD for Mule (Maven, Git, Jenkins / GitHub Actions / Azure DevOps).
• Experience writing MUnit test cases.
• Solid understanding of error handling, retry / dead-letter patterns, security (OAuth 2.0, JWT, mTLS), and observability (logging, monitoring, alerting).
• Proven track record of working directly with US-based clients in a customer-facing capacity.
• Excellent verbal and written English communication — must be comfortable leading technical discussions with US stakeholders.
• Mandatory availability during US EST hours up to 1:00 PM EST (≈ up to 10:30 PM IST).

Good to Have:

• MuleSoft certifications (e.g., MCD – Developer Level 1 / Level 2, MCD – Integration Architect, MCD – Platform Architect).
• Prior experience integrating Oracle EBS / Oracle Fusion or similar Oracle source systems into Salesforce.
• Exposure to Salesforce Order Management or Salesforce CPQ data structures.
• Experience with cloud platforms (AWS / Azure / GCP).
• Familiarity with adjacent ETL / iPaaS tools (Informatica, Talend, Boomi).
• Experience with Agile methodologies and DevOps practices.

What the Platform Offers:

• Vetted Opportunities: Work with top global companies and exciting projects tailored to your expertise.
• Flexible Engagement: Choose between part-time, contract, or full-time roles based on your availability and career goals.
• Global Exposure: Collaborate with clients across industries, gaining diverse experience in the Salesforce and integration ecosystem.
• Supportive Ecosystem: Access a robust network of support from BlueHippo.io, including professional growth resources and mentorship.
• Time Zone Alignment: Work within US time zones, ensuring seamless collaboration with international teams.

The Engineering Challenge
You will be responsible for architecting and building the engine from the ground up. You must solve three specific constraints:

1. The Data Reality: You will not have clean studio data. You must build a pipeline that can ingest "noisy" real-world audio (radio archives, podcasts, street interviews) and autonomously clean, align, and diarize it to create a high-fidelity training set.
2. The Linguistic Complexity: The model must handle Code-Switching (fluidly mixing two languages in one sentence) and Tonal markers without breaking prosody. You must understand how to modify tokenizers to respect these nuances.
3. The Inference Economics: We are not burning venture capital on infinite compute. You must quantize and optimize the model to run on consumer-grade GPUs with low latency. Efficiency is a constraint, not a nice-to-have.

What You Will Own

• End-to-End Pipeline: From raw audio ingestion to served API response.
• Model Fine-Tuning: Adapting foundation models to highly specific, low-resource dialects.
• Inference Architecture: Building a stateless, containerized inference server that handles concurrent requests with sub-200ms latency.

The DNA We Need

• Systems Thinker: You don't just train models; you build products. You understand how the model sits inside a container, how the API handles backpressure, and how the tokenizer affects the runtime.
• Data Realist: You know that 80% of the work is in the dataset. You are comfortable writing custom scripts to slice, denoise, and filter terabytes of audio.
• First-Principles Optimiser: You understand why a model is slow. You are comfortable with quantization, distillation, and kernel-level optimizations to squeeze performance out of limited hardware.

Who You Are (Must-Haves)

• 5 plus years building ML or applied AI systems in production
• Startup experience working on a core product, not a side project
• Strong Python skills and experience integrating with backend systems
• Hands-on experience with AI-assisted coding tools like Cursor or Claude Code
• Fintech experience or strong personal investment background
• Comfortable owning outcomes, not just tasks

Nice-to-Haves (Not Deal Breakers)

• Experience with LLM reasoning systems or knowledge graphs
• Exposure to Golang-based ML integrations
• Prior experience supporting investor-facing products

Qualifications

• 5+ years of experience as a senior engineer in production systems.
• Strong backend and systems design skills.
• Hands-on experience with LLM APIs, agent frameworks, or RAG pipelines.
• Experience building real-time systems (WebSockets, pub/sub, queues).
• Strong knowledge of TypeScript, Python, Go, or similar backend languages.
• Experience with cloud-native architectures and event-driven systems.
• You care deeply about latency, reliability, and correctness.
• Product-minded: you think in workflows, not demos.
• Comfortable working in fast-moving, high-ownership environments.
• Excellent communication and collaboration skills.

• You have 5+ years of experience in a highly quantitative, hands-on role (Actuarial Science, Healthcare Data Science, or ML Engineering) with a track record of shipping production-grade analytical or AI solutions.
• You possess Government Programs Exposure: Direct experience or exposure to health insurance economics, claims, and risk adjustment within Medicare Advantage, Medicaid, or ACA/Marketplace environments.
• You have Modern AI Experience: Experience with LLMs or Generative AI in healthcare or insurance workflows, particularly where explainability, auditability, and operational adoption are critical.
• You are Technically Fluent: High proficiency in Python and SQL, with practical experience developing, deploying, and maintaining AI models in an operational environment.
• You possess Business Intuition: You understand the "why" behind the numbers—you can connect a data anomaly to its underlying financial or actuarial impact without needing a translator.

Skills and Experience

• 3 or more years of full-time experience working in a structured product development environment on a product that had frequent releases
• Hands-on experience with LLM APIs (e.g., OpenAI, Anthropic, Google) and/or AI agent frameworks — including prompt engineering, context management, and evaluation
• Experience with modern programming languages (in this role, you’ll use both Python and TypeScript), as well as experience with AI-enabled coding
• A strong understanding of both the scientific method and software engineering principles, with a proven ability to balance experimental rigor and rapid production deployment
• Experience collaborating with partners from different job functions, and the ability to translate business requirements into technical builds
• Ability to thrive in an entrepreneurial environment, showing a tendency toward speed and action while achieving clarity from ambiguity

Nice to Have:

• Experience with conversational AI voice agents
• A track record of transforming raw, unstructured data sources into actionable intelligence 
• Experience in healthcare, healthtech, or other regulated domains

What We’re Looking For

Required Mindset

• Curious about how AI systems “think” and retrieve information
• Comfortable experimenting and iterating
• Able to explain complex systems simply

Skills & Experience

• Experience with:
  • SEO, content strategy, or technical SEO
  • OR AI/LLMs, prompt engineering, or knowledge graphs
• Strong understanding of:
  • Semantic search
  • Entity-based SEO
  • Content structuring
• Familiarity with tools like:
  • Google Search Console
  • Ahrefs / SEMrush / Similar
  • AI chat tools (ChatGPT, Perplexity, Gemini, Claude)

What We’re Looking For

• 5+ years of experience in AI research, with a strong background in LLM research
• Advanced proficiency in Python and hands-on experience with leading frameworks and libraries, such as PyTorch, Hugging Face, torchtune, and vLLM
• M.Sc. or Ph.D. in Computer Science, Data Science, Statistics, Engineering, Mathematics, Physics, or a related field. Preferably with applied focus on machine learning, computer vision, NLP, or deep learning
• Fast learner with excellent problem-solving skills
• Positive attitude, intellectual curiosity, and eagerness to learn and share knowledge
• Passion for medicine, health, and wellbeing, with a drive to make a meaningful impact
• Proven experience translating deep learning research into reliable, high-impact production systems
• Collaborative team member who contributes to shared technical decisions and knowledge sharing
• (Preferred) Experience with medical data or medical AI

We’d Love for You to Have:

• Eight plus years experience with AI/ML: Deep understanding of machine learning techniques, especially those applicable to healthcare
• Healthcare Expertise: Substantial experience in healthcare technology, clinical workflows, or related fields
• Production AI Experience: Proven track record of taking AI models / products from concept to production in complex environments
• Technical Leadership: Experience leading data science and engineering teams
• Business Acumen: Ability to translate technical capabilities into tangible business value
• Collaborative Mindset: Ability to work effectively with diverse teams, holding strong opinions loosely and valuing input from others
• Communication Skills: Exceptional ability to communicate complex AI concepts to diverse audiences
• Regulatory Knowledge: Familiarity with healthcare regulations affecting AI deployment (HIPAA, FDA, etc.)
• Ethics & Governance: Strong understanding of ethical AI principles and governance frameworks

What You’ll Do:

• Own multiple projects from end to end: brainstorming product concepts, generating POCs to be evaluated and owning builds to reach a minimum viable product.
• Build full-stack applications (backend, frontend, data layer, infra, deployment, and monitoring).
• Experiment with AI functionality on each case: classical ML when needed (forecasting, scoring, classification), plus LLM/agent workflows and evaluation loops
• Establish engineering standards: code quality, CI/CD hygiene, logging/analytics, basic security
• Work directly with design partners and ship weekly updates

Requirements

• You should have:

  • 3+ years shipping full-stack products end-to-end
  • Strong Python and modern web stack (React/Next.js + APIs + DB + deployments)
  • Data processing and Machine learning fundamentals (pandas, Sklearn, pytorch/tensorflow, model evaluation)
  • Experience experimenting with LLMs and Agent frameworks (Open AI SDK, Google ADK, Langchain/Langraph, MCP)
  • Comfort with ambiguity, fast cycles, and customer-facing iteration

• What Success Looks Like:

  • Ship multiple POCs that clearly validate feasibility and ROI
  • Bring at least one concept to a usable MVP with design-partner feedback loops

What You'll Do 

• Design, architect, and deploy AI-powered systems that directly impact member experience and operational efficiency
• Build and optimize LLM-driven applications using advanced prompt engineering, RAG architectures, and agentic workflows
• Design scalable AI pipelines using modern orchestration frameworks (LangChain, LangSmith, LlamaIndex, etc.)
• Architect multi-agent systems capable of reasoning, planning, and executing complex multi-step tasks
• Implement evaluation and monitoring frameworks to measure AI performance, detect hallucinations, and ensure reliability at scale
• Own cloud-native AI infrastructure for performance, scalability, cost efficiency, and security
• Partner with Product and Engineering leadership to identify and execute high-impact AI initiatives
• Stay at the frontier of the AI ecosystem and translate emerging capabilities into production-ready systems
• Establish internal standards, tooling, and best practices for AI development across the organization

What You'll Bring 

• Bachelor’s or Master’s degree in Computer Science, Information Systems, Business Administration, or a related field
• 5+ years of professional software engineering experience, including meaningful ownership of production systems
• Significant hands-on experience building and deploying AI/ML systems in production
• Strong proficiency in Python and TypeScript (Next.js a plus)
• Deep experience with LLM APIs (OpenAI, Anthropic, AWS Bedrock) and orchestration frameworks (LangChain, LangSmith, LlamaIndex)
• Strong understanding of advanced prompt engineering techniques and LLM optimization strategies
• Experience designing and deploying RAG systems, vector databases, and semantic search applications
• Cloud infrastructure expertise (AWS preferred): Lambda, Step Functions, API Gateway, DynamoDB, S3
• Strong understanding of LLM behavior: tokenization, embeddings, context limits, evaluation, and hallucination mitigation
• Demonstrated track record of shipping scalable, production-grade AI systems — not prototypes or demos

Nice to Have

• Experience with infrastructure as code (AWS CDK, SAM, Terraform)
• Experience in healthcare, insurance, or regulated environments
• Experience fine-tuning models or building custom model pipelines
• Familiarity with observability tools (DataDog, CloudWatch, LangSmith)
• Contributions to open-source AI projects or published technical work

• Design and execute the enterprise AI enablement strategy, ensuring employees have the skills and confidence to leverage AI tools for productivity, efficiency, and innovation
• Lead the rollout and adoption of enterprise AI tools, partnering with IT, Communications, and business leaders to drive engagement and measurable impact
• Create learning pathways, resources, and just-in-time training that meet employees where they are—from AI-curious to power users
• Develop AI fluency programs that help employees understand when and how to use AI effectively, including prompt engineering, workflow integration, and critical evaluation of AI outputs
• Establish metrics and feedback loops to measure AI adoption, productivity gains, and employee confidence

• Design, build, and facilitate leadership development programs that meet leaders where they are in their leadership journey—from first-time managers stepping into leadership for the first time to senior leaders driving enterprise strategy
• Upskill leaders on the high-value human work of leadership: building trust, developing talent, having courageous conversations, coaching for performance, and creating environments where people do their best work
• Enable leaders to leverage AI tools effectively so they can spend less time on administrative tasks and more time on the work that matters—leading, developing, and connecting with their teams
• Partner with People Business Partners to identify leadership capability gaps and design targeted interventions
• Facilitate workshops, cohort programs, and experiential learning, and build scalable resources—toolkits, guides, self-directed learning—that support leaders in the moments that matter

• Rethink and transform the Learning & Development function through an AI-first lens
• Leverage AI to create more personalized, efficient, and impactful learning experiences
• Build systems that enable continuous learning, just-in-time support, and knowledge sharing across the organization
• Partner cross-functionally to embed learning and development into the employee journey

• 7+ years of experience in Learning & Development, Organizational Development, or a related field, with progressive responsibility
• 3+ years of experience designing and facilitating leadership development programs
• Demonstrated experience with AI enablement, digital transformation, or technology adoption initiatives
• Strong AI fluency—not just understanding what AI can do, but hands-on experience using AI tools to enhance your own work and helping others do the same
• Track record of designing and delivering training programs that drive measurable behavior change
• Experience working in fast-paced, high-growth, or transformation environments

• Strategic thinking: Ability to connect workforce development initiatives to business outcomes
• Facilitation excellence: Skilled at designing and leading engaging workshops, training sessions, and cohort experiences for diverse audiences, including senior leaders
• AI-native mindset: Comfortable experimenting with AI tools, staying current on capabilities, and translating technology into practical applications for non-technical audiences
• Human-centered approach: Deep belief that technology should amplify human potential, not replace human connection
• Strong communication: Ability to make complex topics accessible and inspire action across all levels of the organization
• Data-driven: Comfort with measuring impact and using data to iterate on programs
• Collaboration: Proven ability to partner across functions (IT, Communications, HR, business leaders) to drive enterprise initiatives

• Experience in healthcare, technology, or high-growth startup environments
• Familiarity with enterprise AI tools (e.g., Microsoft Copilot or similar)
• Coaching certification or executive coaching experience
• Experience with instructional design and adult learning principles
• Background in change management methodologies

You Will: Key Responsibilities & Impact

• Architect and build next-generation Conversational AI products that push the boundaries of what's possible
• Lead and mentor engineering teams, setting technical direction and best practices
• Partner with Product to shape requirements and translate vision into scalable solutions
• Design cloud-native architectures that are resilient, scalable, and built for the future
• Integrate cutting-edge AI tools and services, championing their adoption across the team
• Drive engineering excellence through comprehensive test automation and quality-first delivery

You Have: Required Skills & Qualifications

• 10+ years building full-stack applications with Java and Node.js (Python and Vue.js are a plus)
• Bachelor's or Master's degree in Computer Science, Communications, or related field
• 5+ years designing and architecting enterprise-grade SaaS Products
• 5+ years shipping AI products to production
• Deep experience with cloud platforms (GCP experience is a plus)
• Background in data analytics and reporting tools, especially for contact centers and conversational analytics (nice to have)
• Proven track record leading engineering team as technical expert

Skills and Experience

• 3 or more years of full-time experience working in a structured product development environment on a product that had frequent releases
• Hands-on experience with LLM APIs (e.g., OpenAI, Anthropic, Google) and/or AI agent frameworks — including prompt engineering, context management, and evaluation
• Experience with modern programming languages (in this role, you’ll use both Python and TypeScript), as well as experience with AI-enabled coding
• A strong understanding of both the scientific method and software engineering principles, with a proven ability to balance experimental rigor and rapid production deployment
• Experience collaborating with partners from different job functions, and the ability to translate business requirements into technical builds
• Ability to thrive in an entrepreneurial environment, showing a tendency toward speed and action while achieving clarity from ambiguity

Nice to Have:

• Experience with conversational AI voice agents
• A track record of transforming raw, unstructured data sources into actionable intelligence 
• Experience in healthcare, healthtech, or other regulated domains

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What You Bring

• Proven Track Record in Large Deals: 7+ years managing enterprise sales cycles with experience closing $5M–$20M+ annual agreements spanning multiple concurrent projects.
• Expert in Multi-Threaded Sales: Demonstrated success engaging across research leaders, engineering stakeholders, procurement teams, and C-suite executives.
• Consultative & Strategic Approach: Adept at translating technical needs (AI safety, evals, data quality, benchmarks) into commercial frameworks that resonate with business and technical leaders alike.
• Operational Rigor: Ability to manage complex deal structures, ensure visibility across 20+ active workstreams, and coordinate with internal delivery and product teams to ensure flawless execution.
• Domain Expertise: Experience selling AI, ML, or human-data services to advanced research orgs and technical decision-makers.
• Full-Cycle Deal Leadership: Skilled in qualification, solution design, proposal building, negotiation, procurement navigation, and customer success alignment.
• Executive Communication: Excellent written and verbal communicator with the ability to craft compelling narratives for both technical and business stakeholders.

What You'll Bring

• 8+ years of experience in data science, analytics, or a related AI field
• Strong SQL and Python skills; experience with data visualization tools (e.g., Looker, Tableau, Metabase) for data storytelling
• Experience designing and running A/B tests or correlational analyses
• Familiarity with LLM evaluation methodologies or AI quality assurance
• Experience working with research teams or supporting program evaluation
• Clear communication skills for translating data into insights for non-technical stakeholders

Nice to Have

• Experience in education, workforce development, or public sector contexts
• Familiarity with FERPA, COPPA, or student data privacy requirements
• Experience with knowledge graphs or RAG systems
• Background in qualitative research support or mixed-methods evaluation