Senior Software Developer - MCP and Agentic AI

Design and Development: Participate in the full software development lifecycle, including designing, coding, testing, and debugging of agentic AI frameworks and autonomous systems powered by LLMs for reasoning, decision-making, and tool execution

AI and Machine Learning Integration: Collaborate with engineers and AI specialists to integrate machine learning models, including LLMs, into production applications. Integrate and optimize large language models and RAG pipelines using Lang Chain, FAISS, or similar frameworks to enhance content retrieval

AI Observability: Apply observability tools such as Comet Opik for model tracing, prompt evaluation, and system monitoring

Code Quality: Write clean, maintainable, and efficient Python code while adhering to industry’s best practices. Use AI-assisted development tools like Cursor, Claude Code, or Copilot to accelerate coding and experimentation

Collaboration: Work closely with cross-functional teams to understand requirements, provide technical expertise, and deliver high-quality solutions

Continuous Improvement: Identify areas for improvement in existing systems and make recommendations for enhancements

Scalability: Ensure scalability, security, and reliability of deployed AI services to handle growing data and user demands within AWS environments (Lambda, ECS, Aurora, S3, Bedrock)

Documentation: Maintain comprehensive documentation for new and existing features (APIs, and MCP workflows)

Education: Bachelor’s or Master’s degree in Computer Science, Software Engineering, or a related field

Experience: Minimum of 3 years of professional software development experience, with a focus on AI and machine learning applications

Proficiency in programming languages such as Python, Java, or C++

Experience with AI and machine learning frameworks like Tensor Flow, PyTorch, or similar, Model Context Protocol (MCP) servers, handling tool registration, context sharing, and secure communication between agents

Experience with Large Language Models (LLMs) and their application in software development

Experience with frameworks such as Lang Chain, DySpy, or CrewAI for multi-agent orchestration and contextual reasoning

Experience building large-scale RAG or vector-based storage systems using FAISS, Redis, or comparable tools

Experience with experimentation and observability tools such as Comet Opik or Weights & Biases

Solid understanding of software design principles, algorithms, and data structures

Familiarity with cloud platforms (AWS, Azure, or Google Cloud) and containerization technologies (Docker, Kubernetes)

Strong problem-solving skills and the ability to think critically

Excellent communication and teamwork abilities

Ability to work in a fast-paced, agile environment

A passion for innovation and a strong desire to stay updated with the latest industry trends and technologies

Experience with natural language processing (NLP) and conversational AI would be a plus

Prior experience in working on large-scale, distributed systems

Knowledge of CI/CD pipelines and Dev Ops practices