AI Full Stack Engineer

We are looking for a hands-on AI Full Stack Engineer to join our growing AI Center of Excellence. In this role, you will design, build, and operationalize intelligent AI agents and LLM-powered solutions that drive real business impact. You will work at the intersection of cloud infrastructure, modern AI frameworks, and production-grade software engineering - owning the full lifecycle from prototype to deployment., * Design and develop AI agents - including autonomous, multi-step, and tool-using agents - using AWS Bedrock and leading agentic frameworks.

• Build, fine-tune, and integrate Large Language Models (LLMs) and Small Language Models (SLMs) into production workflows.
• Develop backend services and agent orchestration layers using Node.js and Python.
• Implement agent monitoring, observability, and evaluation pipelines using tools such as Fiddler AI and comparable platforms.
• Collaborate with product and engineering teams to translate business requirements into robust AI-powered features.
• Establish best practices for responsible AI, prompt engineering, model evaluation, and agent safety.
• Continuously evaluate emerging models, frameworks, and tooling to keep the platform at the cutting edge.
• Contribute to internal documentation, architecture reviews, and knowledge sharing across the team.

3+ years of professional software engineering experience, including hands-on experience building AI/LLM-powered applications.

Cloud & Infrastructure

• AWS Bedrock - hands-on experience building and deploying models and agents on the Bedrock platform (foundation model access, Knowledge Bases, Agents for Bedrock).
• Familiarity with broader AWS ecosystem (Lambda, S3, IAM, API Gateway, etc.).

Agent Development

• Proven, hands-on experience building AI agents - including autonomous agents, tool-calling agents, ReAct / plan-and-execute patterns, and multi-agent orchestration.
• Experience with agentic frameworks such as LangChain, LangGraph, AutoGen, CrewAI, or AWS Bedrock Agents.
• Strong understanding of agent memory, context management, and tool use.

Languages & Frameworks

• Python - proficient; used for ML pipelines, agent logic, data processing, and scripting.
• Node.js - proficient; used for API development, backend services, and agent integration layers.

LLM / SLM Expertise

• Hands-on experience working with Large Language Models (e.g., Claude, GPT-4, Llama, Mistral) and Small Language Models (e.g., Phi-3, Gemma, Mistral 7B).
• Practical knowledge of prompt engineering, few-shot learning, RAG (Retrieval-Augmented Generation), and fine-tuning workflows.

Monitoring & Observability

• Experience with Fiddler AI or comparable agent/model monitoring tools (e.g., LangSmith, Arize, Weights & Biases, Helicone).
• Ability to define and track agent performance metrics: accuracy, latency, hallucination rate, tool-call success, and cost.

Preferred Qualifications

• Experience with vector databases (Pinecone, pgvector, OpenSearch, Weaviate) for semantic search and RAG pipelines.
• Familiarity with MLOps practices - CI/CD for models, model versioning, A/B evaluation.
• Exposure to multi-modal models (vision + language).
• Prior work in an AI product or platform team at scale.
• AWS certifications (e.g., AWS Certified Machine Learning - Specialty) are a plus., * Hands-on builder - You write code, ship agents, and debug production issues - not just architect on whiteboards.

• Curiosity-driven - You stay current with the fast-moving AI landscape and bring new ideas to the team.
• Ownership mindset - You take a feature from idea to production and care about it long after launch.
• Clear communicator - You can explain complex AI behavior to non-technical stakeholders without dumbing it down.

Why Join Us

• Work on cutting-edge agentic AI systems that are deployed at enterprise scale.
• Be part of the AI Center of Excellence - a team dedicated to pushing the boundaries of what AI can do inside and outside the organization.
• Collaborative, low-ego culture with a strong bias for shipping. xrbllit
• Competitive compensation, flexible work arrangements, and continuous learning support.