We are looking for an AI Engagement Lead / AI Engineering Pod Lead who can combine strong client and project leadership with hands-on expertise in AI/ML and Generative AI engineering. The role will involve approximately 50% engagement/project management and coordination and 50% hands-on technical leadership and AI engineering.
Responsibilities:- Lead AI/GenAI engagements from discovery and solution definition through development, deployment, and production.
- Serve as the primary technical and delivery interface for clients and senior stakeholders.
- Understand business objectives and translate them into AI/ML solution requirements and actionable engineering plans.
- Own project planning, prioritization, timelines, milestones, risks, dependencies, and overall delivery.
- Coordinate across AI Engineers, Data Scientists, Data Engineers, Product Managers, and client teams.
- Conduct regular client discussions, status reviews, technical walkthroughs, and solutioning sessions.
- Proactively identify delivery risks, technical challenges, resource constraints, and dependencies and drive them toward resolution.
- Architect, develop, and deploy AI/ML and Generative AI solutions for enterprise use cases.
- Lead hands-on development of LLM-powered applications, RAG systems, AI agents, and agentic workflows.
- Design and implement end-to-end AI application architectures, including: LLM integration, Prompt engineering, RAG pipelines, Embeddings and vector databases, Tool/function calling, Agent orchestration, Evaluation and monitoring
- Work with frameworks such as LangChain, LangGraph, LlamaIndex, Semantic Kernel, or equivalent technologies.
- Integrate foundation models and LLM platforms such as OpenAI, Azure OpenAI, Anthropic Claude, Amazon Bedrock, Gemini, or open-source models.
- Develop production-grade AI services and APIs using technologies such as Python, FastAPI, Docker, Kubernetes, and cloud platforms.
- Design retrieval pipelines including document processing, chunking, embedding generation, vector search, hybrid retrieval, and re-ranking.
Requirements- 10+ years of experience in software engineering, AI/ML engineering, data science, or a related technical field.
- Strong hands-on experience building and deploying AI/ML or Generative AI solutions.
- Proven experience leading technical teams or AI engineering pods while remaining hands-on.
- Strong proficiency in Python and experience developing production-grade applications.
- Strong understanding of LLMs, Generative AI, NLP, RAG, and AI agents.
- Experience with one or more AI/GenAI frameworks such as LangChain, LangGraph, LlamaIndex, Semantic Kernel, or equivalent.
- Experience working with LLM APIs/foundation models such as OpenAI, Azure OpenAI, Anthropic, Bedrock, Gemini, or open-source LLMs.
- Experience with vector databases and semantic search.
- Experience designing and deploying cloud-based AI solutions on AWS, Azure, or GCP.
- Strong understanding of APIs, microservices, Docker, CI/CD, and production deployment.
- Experience with AI evaluation, monitoring, guardrails, and responsible AI is highly desirable.
- Strong client-facing communication and stakeholder management skills.
- Demonstrated ability to translate ambiguous business problems into practical technical solutions.
- Master's in Business Analytics or equivalent work experience.
BenefitsSignificant career development opportunities exist as the company grows. The position offers a unique opportunity to be part of a small, fast-growing, challenging and entrepreneurial environment, with a high degree of individual responsibility.
