Technical Lead AI Initiatives

About your role:

We are seeking a highly skilled Technical Lead for AI Development to drive the architecture, design, and execution of advanced AI systems using LLM frameworks, multi-agent architectures, RAG pipelines, and Model Context Protocol (MCP) integrations. The ideal candidate has strong hands-on experience building production-grade AI features, orchestrating agent ecosystems, evaluating model performance, and iterating through continual refinements.

You will lead a team of engineers, collaborate with product and research teams, and play a key role in shaping our AI strategy and platform capabilities.

Key Responsibilities:

AI Architecture & Development

• Design and implement multi-agent systems, including agent orchestration, delegation, and tool interaction patterns.
• Build scalable RAG (Retrieval-Augmented Generation) architectures using vector databases, embedding pipelines, and data chunking strategies.
• Integrate and extend MCP (Model Context Protocol) tools for robust model-tool communication and workflow automation.
• Lead development of AI-based features, prototypes, and production solutions using LLM APIs or self-hosted models.
• Architect and optimize prompt engineering, prompt chains, agent loops, and refinement pipelines.

Model Evaluation & Continuous Improvement

• Implement and maintain agent evaluation frameworks (agent evals, scenario tests, regression testing).
• Design automated evaluation harnesses for LLM quality, reliability, hallucination control, and performance metrics.
• Drive iterative improvements through A/B testing, reward models, and feedback loops.
• Monitor system performance, latency, cost, and reliability — and implement optimization strategies.

Technical Leadership

• Lead and mentor engineers working on AI, data, and backend components.
• Collaborate with product managers, researchers, and cross-functional teams to align tech strategy with business outcomes.
• Conduct code reviews, enforce best practices, and maintain architectural standards.
• Own technical roadmaps, sprint planning, and engineering execution.

Systems & Infrastructure

• Work with cloud platforms (AWS/GCP/Azure) to deploy scalable AI services.
• Integrate vector databases (Pinecone, Weaviate, Elasticsearch, etc.).
• Build APIs and microservices to expose AI capabilities to internal and external stakeholders.
• Maintain secure, compliant, and efficient data pipelines for ingestion and retrieval.

Qualifications

• Bachelor’s/Master’s degree in Computer Science, Engineering, AI, or related field.
• 8+ years of software engineering experience with strong backend architecture skills.
• 3+ years deep experience with LLMs, GPT models, agents, or advanced ML systems.
• Strong hands-on experience with:
• MCP tools and LLM tool integration
• Agent frameworks (e.g., OpenAI Agents, LangChain, LlamaIndex, custom agents)
• RAG pipelines, embedding models, vector stores
• Agent evaluation, reliability testing, and model refinements
• Proficiency in Python, TypeScript/Node.js, or similar languages.
• Experience deploying LLM apps and APIs in production environments.
• Deep understanding of AI limitations, hallucination control, and safety measures.

Preferred / Nice to Have

Experience with:

• Fine-tuning LLMs
• OpenAI API, Claude, or Azure OpenAI
• Distributed embeddings and high-throughput retrieval systems
• MLOps frameworks
• Knowledge of DevOps, CI/CD, containerization (Docker/Kubernetes).
• Prior leadership experience managing small to mid-size engineering teams.

Thank you!