Location
Job description
Role: Senior AI/ML Engineer - Automotive client EXP MUST Location: Santa Clara Valley, CA Work Model: Hybrid (3 days a week) Contract 12+ months Rate is $60/hr on C2C/1099 Client – Tech Mahindra
Only H1B
11+ years of experience with any Automotive clients like Ford Motor Company
Job Description:Background: Looking for an experienced AI Engineer to design, build, and deploy enterprise-grade AI solutions for customers. The ideal candidate should have hands-on expertise with Retrieval-Augmented Generation (RAG), Agentic AI workflows, and LLM-based automation, with the ability to integrate AI systems into complex enterprise environments.
Responsibilities:Build and optimize RAG pipelines, vector databases, embeddings, and document-processing workflows.Design agentic AI systems (tool calling, orchestration, reasoning loops, workflow automation).Develop Applied AI solutions that integrate with customer backend systems, APIs, and data sources.Implement AI services on Kubernetes, cloud environments, or customer-controlled infrastructure.(Good to have) Integrate AI workflows with PLM systems or enterprise knowledge platforms.Work directly with customers to deliver high-quality technical implementations, demos, and documentation.
Required Skills:Strong experience with LLMs, LangChain / LlamaIndex / custom agent frameworks.Expertise in Python, vector DBs (Elastic, Milvus, Pinecone, etc.), embeddings, chunking.Experience with Kubernetes, Docker, and scalable API deployment.Ability to understand customer workflows and translate them into technical solutions.
Nice to Have:Knowledge of PLM, PDM, or enterprise engineering workflows.Experience with RAG evaluation, prompt engineering, and grounding strategies.Familiarity with enterprise architecture, IAM, SSO, or security constraints
Only H1B
11+ years of experience with any Automotive clients like Ford Motor Company
Job Description:Background: Looking for an experienced AI Engineer to design, build, and deploy enterprise-grade AI solutions for customers. The ideal candidate should have hands-on expertise with Retrieval-Augmented Generation (RAG), Agentic AI workflows, and LLM-based automation, with the ability to integrate AI systems into complex enterprise environments.
Responsibilities:Build and optimize RAG pipelines, vector databases, embeddings, and document-processing workflows.Design agentic AI systems (tool calling, orchestration, reasoning loops, workflow automation).Develop Applied AI solutions that integrate with customer backend systems, APIs, and data sources.Implement AI services on Kubernetes, cloud environments, or customer-controlled infrastructure.(Good to have) Integrate AI workflows with PLM systems or enterprise knowledge platforms.Work directly with customers to deliver high-quality technical implementations, demos, and documentation.
Required Skills:Strong experience with LLMs, LangChain / LlamaIndex / custom agent frameworks.Expertise in Python, vector DBs (Elastic, Milvus, Pinecone, etc.), embeddings, chunking.Experience with Kubernetes, Docker, and scalable API deployment.Ability to understand customer workflows and translate them into technical solutions.
Nice to Have:Knowledge of PLM, PDM, or enterprise engineering workflows.Experience with RAG evaluation, prompt engineering, and grounding strategies.Familiarity with enterprise architecture, IAM, SSO, or security constraints