AI Technical Lead - Machine Learning
First seen by Alion on Aug 11, 2026.
Job Description :
We are looking for an AI Technical Lead with 6 to 11 years of experience to design and deliver enterprise-grade AI solutions using Generative AI, Multi-Agent Systems, RAG, MCP, and LLM fine-tuning. The ideal candidate should combine strong hands-on expertise in AI engineering and architecture with the ability to lead technical teams and drive end-to-end enterprise AI initiatives.
Key Responsibilities :
- Design and define scalable AI architectures for enterprise use cases involving LLMs, RAG, Multi-Agent Systems, and AI-powered applications.
- Architect and develop Multi-Agent Systems with effective agent orchestration, tool integration, memory, and workflow management.
- Design and implement RAG pipelines, including document ingestion, chunking, embeddings, vector search, retrieval, reranking, and context management.
- Build and integrate solutions using Model Context Protocol (MCP) and other mechanisms for connecting AI models with enterprise tools, systems, and data sources.
- Design and implement LLM fine-tuning and model adaptation strategies based on business requirements and domain-specific use cases.
- Apply context engineering techniques to improve model accuracy, relevance, reliability, and response quality.
- Develop scalable AI applications and supporting data pipelines using Python and modern AI/ML frameworks.
- Design knowledge graphs and structured knowledge representations to support intelligent retrieval and reasoning.
- Integrate LLMs with enterprise applications, APIs, databases, and external tools.
- Establish practices for prompt engineering, evaluation, observability, guardrails, security, and responsible AI.
- Drive AI solution deployment across cloud and enterprise environments with focus on scalability, performance, reliability, and cost optimization.
- Lead technical discussions, architecture reviews, and design decisions across AI engineering teams.
- Mentor engineers and provide technical direction on AI architecture, development, and deployment practices.
- Collaborate with product, data, engineering, security, and business stakeholders to translate business requirements into scalable AI solutions.
- Evaluate emerging AI technologies and frameworks and identify opportunities to improve enterprise AI capabilities.
Required Skills & Experience:
- 6-11 years of experience in AI/ML, software engineering, or related technical domains, with significant hands-on experience in Generative AI.
- Strong hands-on experience with Multi-Agent Systems, RAG, MCP, and LLM-based application development.
- Experience with LLM fine-tuning, model adaptation, prompt engineering, and context engineering.
- Strong proficiency in Python and experience with AI/ML development frameworks.
- Strong understanding of LLM architecture, embeddings, vector databases, retrieval techniques, and AI application patterns.
- Experience designing enterprise AI architectures and taking solutions from proof of concept to production.
- Experience building scalable data and knowledge pipelines for AI applications.
- Good understanding of knowledge graphs, semantic search, and structured/unstructured data processing.
- Experience with LLM evaluation, monitoring, guardrails, and AI application performance optimization.
- Strong understanding of APIs, microservices, cloud platforms, and scalable deployment architectures.
- Proven ability to lead technical teams and drive architecture and engineering decisions.
- Strong communication, stakeholder management, and problem-solving skills.
Preferred Skills :
- Experience with frameworks such as LangChain, LangGraph, LlamaIndex, Semantic Kernel, or similar.
- Experience with MCP servers, tools, and enterprise integrations.
- Hands-on experience with vector databases such as Pinecone, Milvus, Weaviate, pgvector, or equivalent.
- Experience with cloud AI platforms such as AWS Bedrock, Azure OpenAI, or Google Vertex AI.
- Exposure to MLOps, CI/CD, Docker, Kubernetes, and production AI observability.
- Experience delivering AI solutions in large enterprise environments.
Skills
Artificial Intelligence, Machine Learning, LLM, RAG, Python, Generative AI, SQL, ETL