Senior Associate - AI Full Stack Engineer
About The Position
We are seeking an experienced AI Full Stack Engineer to design, build, and deploy next-generation AI-powered applications. This role operates at the intersection of machine learning, agentic AI, and full-stack development, delivering scalable solutions that embed intelligence directly into business workflows. The AI Full Stack Engineer will partner with product managers, data scientists, architects, and DevOps teams to translate ambiguous business problems into production-ready systems. You will work across the full stack — from AI/ML model development and deployment to frontend user experiences and backend services — ensuring that solutions are performant, secure, and aligned with enterprise standards. This position is ideal for engineers with strong software craftsmanship, applied AI/ML experience, and a passion for agentic AI systems and Retrieval-Augmented Generation (RAG) architectures.
Requirements
- Master’s degree in Computer Science, Machine Learning, Data Science, Software Engineering, or related technical field.
- 4+ years of professional software development experience, with at least 2+ years focused on AI/ML application development and deployment.
- Proficiency in modern frontend frameworks (React, Angular, Vue), backend development (Python, Node.js, Java, Go), and RESTful APIs.
- Strong experience with SQL and NoSQL databases.
- Hands-on experience deploying applications to AWS, GCP, or Azure.
- Proven expertise with Git, CI/CD pipelines, Docker, and Kubernetes.
- Solid understanding of ML pipeline automation, model versioning, and production deployment.
- Strong collaboration and communication skills to work with technical and business partners.
Nice To Haves
- Experience implementing RAG systems and working with vector databases (Pinecone, Weaviate, ChromaDB).
- Proficiency in agent development frameworks (LangChain, LlamaIndex, Strands) and multi-agent orchestration.
- Familiarity with real-time AI systems, streaming pipelines, and low-latency inference using Kafka or Redis Streams.
- Knowledge of monitoring ML systems for drift, performance degradation, and automated alerting.
- Exposure to insurance or financial services technology solutions.
- Demonstrated ability to lead technical projects and mentor junior engineers.
- Strong portfolio of AI-enabled full-stack applications in production.
Responsibilities
- Design and implement end-to-end AI-powered applications, from data pipelines and ML models to APIs and user interfaces.
- Collaborate with product managers and stakeholders to translate business problems into technical specifications.
- Build and optimize RAG systems leveraging embeddings, vector databases, and document pipelines.
- Develop AI agents with autonomous reasoning, multi-step task execution, and external tool/API integration.
- Implement Agentic AI protocols including Model Context Protocol (MCP) and multi-agent orchestration frameworks.
- Build scalable frontend applications using React, Angular, or Vue, and backend services with Python, Node.js, Java, or Go.
- Design and maintain SQL and NoSQL databases (PostgreSQL, MySQL, MongoDB, Redis) for structured and unstructured data.
- Deploy, monitor, and scale applications on cloud platforms (AWS, GCP, Azure) with Docker and Kubernetes.
- Implement CI/CD pipelines, version control, and automated testing for reliable delivery.
- Ensure system reliability through monitoring, observability, drift detection, and alerting for ML models in production.
- Collaborate with data scientists, DevOps, and cross-functional teams to accelerate AI feature delivery.
- Mentor junior developers and contribute to a culture of engineering excellence.
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
