Gen AI Engineer c2c requirements Boston, MA

Job Title- Gen AI Engineer

Location: Boston, MA (Hybrid 3 days to work at client location)

Type: : Long Term Contract

Industry: AI/ML, Enterprise Applications, Healthcare (if applicable)

Must: Strong in python and have experience designing and develop GenAI enabled solutions

Role Summary:

We are seeking an experienced GenAI Engineer to integrate LLM APIs, build AI-driven applications, optimize model performance, and deploy AI services at scale. The ideal candidate has expertise in Python-based AI development, LLM orchestration, cloud deployment, and enterprise AI integration.

Key Responsibilities:

• AI Application Development: Build and maintain Python-based AI services using LangChain and CrewAI. Implement RAG-based retrieval and Agentic AI workflows.

• LLM Integration & Optimization: Integrate OpenAI, Bard, Claude, Azure OpenAI APIs. Optimize API calls using temperature, top-p, max tokens, and reduce hallucinations using embedding-based retrieval (FAISS, Pinecone).

• Model Evaluation & Performance Tuning: Assess AI models using Model Scoring, fine-tune embeddings, and enhance similarity search for retrieval-augmented applications.

• API & Microservices Development: Design scalable RESTful API services. Secure AI endpoints using OAuth2, JWT authentication, and API rate limiting.

• Cloud Deployment & Orchestration: Deploy AI-powered applications using AWS Lambda, Kubernetes, Docker, CI/CD pipelines. Implement LangChain for AI workflow automation.

• Agile Development & Innovation: Work in Scrum teams, estimate tasks accurately, and contribute to incremental AI feature releases.

Tech Stack & Tools:

• AI/ML: PyTorch, TensorFlow, Hugging Face, Pinecone

• LLMs & APIs: OpenAI, LangChain, CrewAI

• Cloud & DevOps: AWS, Azure, Kubernetes, Docker, CI/CD

• Security & Compliance: OAuth2, JWT, HIPAA

Preferred Qualifications:

• 9+ years of overall experience with a minimum of 4 years in AI/ML, LLM integrations, and enterprise cloud solutions.

• Proven expertise in GenAI API orchestration, prompt engineering, and embedding retrieval.

• Strong knowledge of scalable AI architectures and security best practices.