Posted on
August 24th, 2026
Location
Hyderabad
Type
Full-time, Permanent
Experience
7+ years
Open Positions
1
About the Role
We are looking for a hands-on Lead AI/ML Engineer to lead the architecture, development, and evolution of our AI platform.
This role combines AI engineering, machine learning, technical architecture, and team leadership. You will lead AI Developers and ML Engineers while remaining hands-on in designing and building production AI/ML systems.
You will be responsible for the complete AI technology stack, from LLMs, RAG, AI agents, and intelligent applications to embeddings, retrieval systems, evaluation frameworks, data pipelines, and production monitoring.
This is a hands-on technical lead role. Candidates whose experience is primarily people management, project management, or AI strategy without recent hands-on experience building production AI/ML systems will not be a fit.
This role combines AI engineering, machine learning, technical architecture, and team leadership. You will lead AI Developers and ML Engineers while remaining hands-on in designing and building production AI/ML systems.
You will be responsible for the complete AI technology stack, from LLMs, RAG, AI agents, and intelligent applications to embeddings, retrieval systems, evaluation frameworks, data pipelines, and production monitoring.
This is a hands-on technical lead role. Candidates whose experience is primarily people management, project management, or AI strategy without recent hands-on experience building production AI/ML systems will not be a fit.
Responsibilities:
- Lead the architecture and development of production AI/ML systems, including LLM applications, RAG, AI agents, intelligent workflows, retrieval systems, and automation.
- Remain hands-on with Python and AI/ML development, including building solutions, reviewing code, debugging complex issues, and solving production problems.
- Own architecture and technology selection across LLMs, models, embeddings, vector databases, retrieval, agents, APIs, data pipelines, model integration, and ML systems.
- Design and continuously improve retrieval, evaluation, and experimentation systems to optimize accuracy, relevance, hallucination, latency, reliability, scalability, and cost.
- Lead and mentor AI Developers and ML Engineers, establish engineering standards, review technical approaches and code, and make key architecture and technology decisions.
- Take technical ownership of AI/ML solutions from business requirements and experimentation through deployment, monitoring, and continuous improvement.
Experience & Qualifications:
- 7+ years of professional experience in software engineering, machine learning, data science, Applied AI, or related technical roles, including at least 5+ years of hands-on AI/ML experience and recent experience with Generative AI, with at least 3 years in a leadership role.
- Deep hands-on proficiency in Python and SQL, with experience building production applications, APIs, AI services, data pipelines, and integrations.
- Deep understanding of LLMs, RAG, embeddings, vector databases, retrieval, prompt/context engineering, structured outputs, tool/function calling, AI agents, and agentic workflows.
- Strong understanding of machine learning fundamentals, statistics, experimentation, model evaluation, information retrieval, ranking, and data quality.
- Hands-on experience building and optimizing RAG, retrieval, and evaluation systems, including chunking, embeddings, vector/hybrid search, metadata filtering, reranking, and performance measurement.
- Hands-on experience with modern AI orchestration and RAG frameworks such as LangGraph, LlamaIndex, or equivalent, including agentic workflows, tool integration, retrieval pipelines, state management, and production AI application design.
- Experience with PyTorch, TensorFlow, or Scikit-learn, along with modern AI frameworks, APIs, and production AI/ML practices.
- Experience with AWS or another major cloud platform, Docker, Git, CI/CD, and demonstrated experience technically leading and mentoring AI/ML engineers.
Nice to Have:
- Experience with MCP (Model Context Protocol), CrewAI, AutoGen, Semantic Kernel, or similar emerging AI and multi-agent technologies.
- Experience with pgvector, Pinecone, Weaviate, FAISS, Milvus, Redis, or similar vector and retrieval technologies.
- Experience with MLflow, Weights & Biases, LangSmith, Arize, Phoenix, or similar evaluation, experimentation, and observability platforms.
- Experience with multi-agent systems, recommendation/ranking systems, semantic search, LLMOps/MLOps, model deployment, inference optimization, or large-scale data systems.
Email your resume to recruitment@haystek.com