Required

Requirements:

Know how to build APIs with Fast APIs
Knows how to code and debug
Clear understanding of the fundamentals of coding (Python)
Technical Problem solving ability
Must have shipped at least one Production app by yourself
Knows how to build UI in Angular / React using AI tools
Tech stack - Python, Fast APIs, AI, LLM, Azure, Angular, React

Key Responsibilities:

Assist in designing, developing, and implementing AI chatbots and virtual assistants using Python.
Work on natural language processing (NLP) tasks such as entity recognition, intent detection, and conversation flow.
Integrate AI models with existing cloud services and backend systems.
Test and optimize chatbot functionality to ensure performance, reliability, and user satisfaction.
Debug and troubleshoot technical issues related to AI systems.
Contribute to improving and scaling existing AI applications.
Stay updated on AI/ML trends, particularly in chatbot and AI assistant technologies.

* What you'll do

• Run rapid-cycle growth experiments across acquisition, activation, conversion, and retention.
• Own performance across outbound email, social channels, communities, partnerships, content, and demos.
• Build and optimize funnels - drive predictable pipeline and revenue growth.
• Partner with CEO, product, and our clients to inform GTM and shape product positioning.
• Define and monitor growth metrics (conversion %, CAC, win rate, churn).
• Conduct competitive research & identify new GTM opportunities.
• Work on creating playbooks that scale repeatable revenue processes.

*Who you are

• Interest in growth, marketing, or GTM (Fintech / SaaS preferred).
• Strong knowledge of Banking and Commercial lending
• Strong analytical mindset; fluent in data tools and experimentation.
• Comfortable executing hands-on: writing campaigns, building automations, running outbound.
• Entrepreneurial, resilient, action-oriented, and bias toward speed and results.
• Excellent communicator, skilled at selling complex value simply.
• Passion for AI & fintech transformation.
• Hungry to build category-defining products from 0→1.

Qualifications

• Proven experience, minimum of 6 years, in software development with a focus on mobile AI and AR
technologies in a fast-growing company, preferrably Venture Backed Series A.
• Strong knowledge of mobile application development (iOS and Android) and frameworks, including
ARKit, ARCore, and CoreML.
• Expertise in computer vision, machine learning, and AI algorithms with practical application in mobile
environments.
• Proficiency in programming languages such as Swift, Java, or Kotlin, and proficiency with relevant
development tools and IDEs.
• A strong portfolio of mobile AI and AR projects and applications showcasing your technical skills and
innovative solutions.
• Excellent problem-solving skills, with a strong ability to analyze and optimize performance.
• Effective communication and collaboration skills, with the ability to work within cross-functional teams.
• Passion for delivering AI products that exceed customer expectations, focusing on quality and speed.
• Exceptional organizational and time-management skills, efficiently prioritizing and managing tasks and
projects.
• An empathetic, collaborative, and adaptable leader fostering a culture of teamwork and innovation.
• Global mindset with an understanding of international markets and industry trends.
• Commitment to diversity, ethical practices, and responsible growth.
• Willingness to lead with an entrepreneurial spirit, recognizing the demands of the startup environment.
• Alignment with MoodMe's commitment to ethics, privacy, and social impact in the growth process.
• Excellent written and verbal English skills.
• Bachelor's degree in Engineering, Computer Science, or a similar relevant field (Master's degree
preferred).

Experience, Skills, Knowledge Requirements

• +5 years of experience in designing, developing, testing, and maintaining scalable architectures using Python.
• A strong experience in leveraging AI and the latest tools to drive innovation and efficiency.
• Extensive experience using Python to develop web applications and back-end services.
• Experience with MCP servers (a big plus, but not mandatory).
• Extensive experience working with REST APIs.
• Experience designing, querying, and optimizing databases, particularly using PostgreSQL.
• Experience with Docker, Git, Azure DevOps, CI/CD pipelines, automated testing, and infrastructure as code.
• Familiarity with Azure Functions, Azure OpenAI, Langchain, and building AI workflows and agents.
• Exposure to GraphQL and C#.
• Experience with prompt engineering and optimizing LLM interactions for accuracy and reliability (It’s not mandatory, but ideally you should be open to shortening the learning curve, since it’s a daily basis task).
• Experience with React.
• Experience working with other developers, quality engineers (QE), ops engineers, and support engineers to ensure smooth deployment and continual operation.
• Experience participating in design discussions with both technical and non-technical audiences.
• Excellent problem-solving skills and attention to detail.
• Familiarity or experience with Agile engineering practices (test-driven development, continuous integration, pair programming, etc).
• Ability to work with legacy systems while contributing to modernization efforts.
• Strong problem-solving skills and a passion for learning and applying new technologies.
• Experience collaborating with technical and non-technical stakeholders.
• Familiarity with Agile methodologies and open-source development practices.

Requirements:

• Non-Negotiable: Verifiable, hands-on experience architecting a platform that generates multi-file code from prompts similar to Bolt.new or Lovable. Direct experience with landing page or website generators is a strong plus.

• Proven ability to design and implement multi-agent AI workflows from a systems perspective.

• Deep expertise with Python/Node.js, LLM APIs, and React/Next.js.

What we are looking for:
Experience building production ready systems using Python and SQL. Familiarity with AI and machine learning tools including large language models. Comfort working with messy real world data. Strong problem solving skills and the ability to figure things out independently. Clear communication skills. You should be able to explain technical concepts simply. A bias toward getting things done over perfection.

Nice to have:
Experience in a consulting or agency environment. Background in sales ops, marketing automation or business operations. Familiarity with no code and low code tools.

Who You Are

• 2+ years working with LLMs - you've written production prompts, understand model quirks, and know what makes agents tick
• You ship code. Python, TypeScript, whatever - you can build evals, write scripts, and prototype integrations quickly
• You're a clear communicator who can help non-technical partners implement technical solutions
• You thrive in ambiguity - partnerships are messy, timelines shift, and you figure it out
• You're responsive and reliable - when a partner pings in Slack, you're on it
• Bonus: You've worked at an AI-native company or have experience with agent frameworks (LangChain, CrewAI, OpenAI Agents SDK, etc.)
• Bonus: You've done developer relations, solutions engineering, or technical partnerships before

What you’ll do

• AI Agent-Building (~70% time)

  • Own and evolve Pascal’s existing AI agents (prompts, structure, tone, memory patterns, guardrails) to support trusted, high-quality coaching relationships
  • Design, launch, and iterate on new AI agents grounded in real leadership and people-development use cases (discovery → design → deployment → iteration)
  • Orchestrate how multiple agents work together so the experience feels cohesive, intentional, and human
  • Rigorously test agents for quality, reliability, and alignment with real customer expectations; diagnose failures and turn them into system-level improvements
  • Record, investigate, and resolve quality issues, providing detailed feedback to improve outcomes.
  • Collaborate with engineering and product on implementation.

• L&D work (~30% time)

  • Provide executive and leadership coaching to select client leaders, using those relationships as a live signal for what the AI should (and should not) do
  • Partner with customers on program design, implementation, and change management so Pascal is meaningfully embedded in how teams work—not bolted on
  • Help clients programmatically design and customize Pascal to support ongoing people programs (e.g., manager enablement, feedback, performance, growth)

Who you are

• You have 5+ years working in leadership development, coaching, or L&D, and you have strong point-of-view about what actually helps leaders change behavior
• You’re already actively experimenting with AI in your work or on your own and have clear opinions about what works, what doesn’t, and why. Ideally, you’ve applied it to build or ship something others have actually used.
• You’re comfortable learning in public: working directly with users, reacting to real feedback, and making judgment calls without a playbook
• You move fast, ship imperfect work, and improve it through use rather than over-design

Nice to have

• Experience in forward-deployed, solutions, or customer-facing product roles.
• Exposure to startups or early-stage teams.
• Familiarity with conversational AI, prompt design, or evaluation.
• ICF coaching certification or formal L&D training.

Requirements for the role

• Deep experience in AI/ML systems and model deployment in real-world edge environments.
• Strong proficiency in Rust, Go, C++, or Python.
• Familiarity with distributed systems, federated learning, or privacy-preserving AI.
• Understanding of edge compute hardware and runtime constraints.
• Previous experience in a startup or scale-up environment.
• Track record of delivering complex distributed or AI systems end-to-end.
• Curiosity for verifiable computing, zero-trust architectures, and data-centric AI design.
• A first-principles mindset --- you care about building foundational systems that will last decades.

WHAT WE'RE LOOKING FOR

A successful applicant for this position will be:

• Deeply experienced in modern ML and AI systems, including OCR, RAG, LLM fine-tuning, prompt engineering, and AI agents
• Highly proficient in Python, with working knowledge of GCP infrastructure and modern ML tooling (e.g. Pandas, HuggingFace, Weights & Biases)
• Intensely product-minded, with a focus on translating models into thoughtful, borderline magical features
• Rapidly iterative, able to design smart tests, analyze outcomes, and refine features quickly
• Ownership-oriented, taking end-to-end responsibility for code quality, feature reliability, and production issues when they arise
• Collaborative and generous, willing and able to partner closely with cross-functional teammates
• Passionate about the potential of AI to build great user experiences; experience in the tax domain is a plus but not required

It’s Important To Us That You Have

• 5+ years of experience in Platform Engineering, DevOps, or Site Reliability Engineering (SRE).

• Proven, hands-on experience building and managing production infrastructure with Terraform.

• Expert-level knowledge of Kubernetes architecture and operations in a large-scale environment.

• Experience with high-performance compute (HPC) job schedulers, specifically Slurm, for managing GPU-intensive AI workloads.

• Experience managing bare metal infrastructure, including server provisioning (e.g., PXE boot, MAAS), configuration, and lifecycle management.

• Strong scripting and automation skills (e.g., Python, Go, Bash).

It Would Be Great if You Had 

• Experience with CI/CD systems (e.g., GitLab CI, Jenkins, ArgoCD) and building developer tooling.

• Familiarity with FinOps principles and cloud cost optimization strategies.

• Knowledge of Kubernetes networking (e.g., Calico, Cilium) and storage (e.g., Ceph, Rook) solutions.

• Experience in a multi-region or hybrid cloud environment.

What We Look For

• M.S. in Computer Science, Engineering, or equivalent practical experience

• 10+ years in large scale distributed systems, ideally supporting more than 100k concurrent users

• Proven experience designing and deploying AI systems at scale in distributed, production environments

• Strong background in integrating LLMs with retrieval systems for real-world use cases

• Understanding of data governance, model safety evaluations, red-teaming, and secure ML practices for regulated domains

• Experience with building systems with information retrieval (relevance & ranking), natural language processing techniques like Named Entity Recognition (NER)

Preferred Qualifications

• Background in defense, national security, or other mission-critical domains

• Experience with orchestrating systems that combine text, structured data, and domain-specific signals

Key Responsibilities

• Build and maintain front-end applications
• Write clean, scalable Python & TypeScript code.
• Use AI tools for faster development and automated testing.
• Collaborate with back-end, AI, and product teams.
• Optimize performance across devices & platforms.

You Might Be a Fit If You…

• Have 4+ years of experience as a software engineer, automation engineer, or technical systems builder

• Have deep experience with agentic architectures, workflow automation platforms (N8n, Zapier, Make), and APIs

• Understand prompt engineering, function-calling, retrieval-augmented generation (RAG), and LLM orchestration

• Are passionate about systems thinking and designing workflows that can scale

• Are an elite debugger and systems optimizer—you can reason through edge cases, flakey agents, and API chaos

• Can balance hands-on work with technical leadership

• Are comfortable in a fast-paced, ambiguous startup environment and thrive under autonomy

• Have a low-ego, high-integrity approach to team collaboration

Qualifications:

• 3+ Years AI Engineering Experience: Proven track record in building and deploying AI-powered applications in production environments.
• Strong with Image & Text Models: Experience working with image generation models (e.g., Stable Diffusion) and text generation models (e.g., LLMs like Llama, GPT).
• RunPod / Cloud Deployment Expertise: Comfortable with containerizing AI services (Docker) and deploying on RunPod, AWS, or similar GPU-based platforms.
• Python Proficiency: Strong coding ability in Python, particularly around AI frameworks such as PyTorch, Hugging Face Transformers, or similar.
• Performance Mindset: Deep understanding of optimization strategies for inference speed, GPU memory management, and cost efficiency.
• Collaborative & Agile: Strong communication skills and experience working in Agile environments, with a focus on iterative development and continuous improvement.

Qualifications

• 4–9 years building production systems with ownership across multiple layers of the stack
• Steep career trajectory with rapid advancement based on exceptional execution and impact
• Recent hands-on build experience – your last role involved architecting and shipping systems, not just managing teams
• Strong technical foundation spanning backend systems, databases, APIs, and user interfaces
• Fluency in Figma/Design Tools – you don't need a designer to visualize your logic
• Experience integrating AI/LLM capabilities into product architectures and workflows
• Proven ability to identify where AI adds genuine value versus where traditional approaches excel
• Experience leading technical teams and coordinating cross-functional engineering efforts
• Ability to design systems holistically, understanding how every piece fits together
• Track record of shipping V1 products from 0-to-1 in weeks, not months. You value shipping working software over perfect architecture.
• Comfortable working with high autonomy in fast-moving, unstructured environments
• Excellent English communication and ability to articulate technical decisions clearly

Qualifications

• 4–9 years building production systems with ownership across multiple layers of the stack
• Steep career trajectory with rapid advancement based on exceptional execution and impact
• Recent hands-on build experience – your last role involved architecting and shipping systems, not just managing teams
• Strong technical foundation spanning backend systems, databases, APIs, and user interfaces
• Fluency in Figma/Design Tools – you don't need a designer to visualize your logic
• Experience integrating AI/LLM capabilities into product architectures and workflows
• Proven ability to identify where AI adds genuine value versus where traditional approaches excel
• Experience leading technical teams and coordinating cross-functional engineering efforts
• Ability to design systems holistically, understanding how every piece fits together
• Track record of shipping V1 products from 0-to-1 in weeks, not months. You value shipping working software over perfect architecture.
• Comfortable working with high autonomy in fast-moving, unstructured environments
• Excellent English communication and ability to articulate technical decisions clearly

What You’ll Do

• Design and build AI data pipelines to process, embed, and retrieve structured and unstructured data.

• Work with LLMs, vector databases, embeddings, and retrieval-augmented generation (RAG) systems.

• Prototype and deploy intelligent query and insight systems.

• Collaborate with front-end and back-end engineers to integrate AI models into the user experience.

• Help define data strategy, model optimization, and scalable architecture.

Who You Are

• You have solid experience with Python, LangChain, Hugging Face, OpenAI / Anthropic APIs, and vector DBs (Pinecone, Weaviate, or similar).

• You’ve built or experimented with LLM-powered applications and know what it takes to make them reliable.

• You understand the importance of data quality, embeddings, and context retrieval.

• You’re driven by curiosity and want to help shape the future of human-AI interaction.