Senior AI Full Stack Developer

Senior AI Full Stack Developer

Location:

Boston, MA

Duration: 6 months

Experience

Required:

5–10 years of software engineering experience

Relevant AI

Experience:

2+ years of hands-on experience with Generative AI, Agentic AI, or AI-powered enterprise applications

Design, develop, and deploy enterprise AI applications, intelligent agents, and data-driven solutions.

Leverage Generative AI, Azure AI services, and modern cloud data platforms.

Develop scalable, secure, and production-ready AI solutions.

Integrate AI capabilities with enterprise data platforms and business applications.

Build AI-powered applications and agentic workflows.

Develop RAG-based knowledge, search, and document intelligence solutions.

Design and develop backend services, APIs, microservices, and integration components.

Integrate AI solutions with enterprise data platforms and business applications.

Develop data pipelines and AI workflows.

Build and deploy intelligent AI agents and enterprise copilots.

Deliver scalable, reliable, and production-ready AI solutions.

Take AI solutions from design and development through production deployment.

Strong hands-on experience with Azure AI Foundry and Azure OpenAI.

Expertise in:

• Retrieval-Augmented Generation (RAG)
• Vector Databases
• Prompt Engineering
• Agentic AI

Experience with Agentic AI frameworks, including:

• Lang Chain
• Semantic Kernel
• CrewAI

Strong proficiency in Python.

Strong experience with Snowflake and SQL.

Experience with data integration and cloud data platforms.

Strong enterprise API and microservices development experience.

Experience integrating AI applications with enterprise systems.

Databricks.

Snowflake Cortex.

Snowflake Cortex Agents.

Azure Machine Learning (Azure ML).

MLOps and model monitoring.

React.

Angular.

Experience in Manufacturing.

Experience in Supply Chain.

Experience in Life Sciences.

Develop Generative AI applications using enterprise-grade LLM technologies.

Build RAG pipelines using vector databases and enterprise knowledge sources.

Develop and optimize prompts for LLM-based applications.

Build agentic workflows using Lang Chain, Semantic Kernel, CrewAI, or similar frameworks.

Integrate Azure OpenAI models into enterprise applications.

Develop AI-powered knowledge management, search, and document intelligence solutions.

Implement AI workflows that integrate with enterprise data and business processes.

Develop scalable data pipelines to support AI and analytics workloads.

Integrate AI solutions with Snowflake-based data platforms.

Write optimized SQL queries for enterprise data processing.

Perform data extraction, transformation, and integration.

Work with structured and unstructured enterprise data.

Build AI-ready datasets and data workflows.

Integrate enterprise data sources with AI applications and services.

Design and develop enterprise-grade backend services.

Build REST APIs and microservices for AI applications.

Develop integration components between AI services and enterprise applications.

Implement scalable and secure API architectures.

Ensure reliability, performance, and maintainability of backend services.

Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related field.

5–10 years of software engineering experience.

2+ years of hands-on experience building:

• Generative AI applications
• Agentic AI solutions
• AI-powered enterprise applications

Experience integrating AI solutions with cloud data platforms and enterprise systems.

Strong software engineering and problem-solving skills.

Hands-on AI engineer capable of independently building AI applications and intelligent agents.

Strong experience with Azure AI Foundry and Azure OpenAI.

Experienced in integrating AI solutions with Snowflake-based data platforms.

Capable of developing RAG pipelines, agentic workflows, AI applications, and data pipelines.

Strong backend, API, microservices, and cloud integration experience.

Able to take AI solutions from architecture and design through development, testing, and production deployment.

Strong ability to deliver scalable, secure, and production-ready enterprise AI solutions.