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 & DevelopmentDesign 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 ImprovementImplement 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 LeadershipLead 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 & InfrastructureWork 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.QualificationsBachelor’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 integrationAgent frameworks (e.g., OpenAI Agents, LangChain, LlamaIndex, custom agents)RAG pipelines, embedding models, vector storesAgent evaluation, reliability testing, and model refinementsProficiency 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 HaveExperience with:Fine-tuning LLMsOpenAI API, Claude, or Azure OpenAIDistributed embeddings and high-throughput retrieval systemsMLOps frameworksKnowledge of DevOps, CI/CD, containerization (Docker/Kubernetes).Prior leadership experience managing small to mid-size engineering teams.

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