Lead Associate - Enterprise Risk Management Level

AI Developer- Agentic Systems and LLM Engineering

In this role, we are seeking a highly skilled AI Developer to design and build next-generation agentic AI systems that can reason, plan, and act autonomously. This role sits at the intersection of LLM engineering, system design, and applied AI, with a strong focus on building scalable, production-grade intelligent agents.

You will work closely with prompt engineers, data scientists, and platform teams to develop AI components that leverage retrieval-augmented generation (RAG), memory systems, and tool integration frameworks.

Responsibilities:

Agentic AI Development

• Design and build AI agents capable of reasoning, planning, and executing tasks autonomously
• Develop modular agent components (planners, executors, evaluators, orchestrators)
• Implement multi-step workflows combining LLMs with external tools and APIs

Framework & System Design

• Build and extend agent frameworks for orchestration, chaining, and decision-making
• Develop memory systems (short-term and long-term) to improve agent context retention
• Implement tool-use capabilities, enabling agents to interact with databases, APIs, and enterprise systems

RAG & Knowledge Systems

• Design and implement Retrieval-Augmented Generation (RAG) pipelines
• Work with embeddings and vector databases to enable semantic search and contextual reasoning
• Optimize document ingestion, chunking, indexing, and retrieval strategies

Collaboration & Integration

• Collaborate with prompt engineers to refine prompts, evaluation strategies, and agent behaviors
• Work with cloud and platform teams to deploy scalable AI services
• Integrate AI solutions into enterprise workflows and applications

Minimum Qualifications

Technical Skills

• Strong programming expertise in Python
• Hands-on experience with LLMs and agentic frameworks (e.g., LangChain, Semantic Kernel, or similar)
• Solid understanding of:
• Embeddings and vector databases (e.g., Pinecone, FAISS, Azure AI Search)
• RAG architectures and pipelines
• Prompt engineering and evaluation techniques
• Cloud & Infrastructure
• Good understanding of the Azure cloud ecosystem, including:
• Azure OpenAI Service
• Azure Functions / App Services
• Azure AI Search or equivalent services
• Experience deploying scalable AI/ML solutions in cloud environments
• System Thinking
• Ability to design modular, scalable, and reusable AI components
• Understanding of state management, memory architectures, and agent orchestration
• Strong problem-solving and analytical thinking
• Ability to work in a cross-functional, fast-paced environment
• Clear communication skills to collaborate with both technical and non-technical stakeholders

Qualifications/ Skills

• Experience building multi-agent systems
• Familiarity with evaluation frameworks for LLMs (hallucination detection, response quality, etc.)
• Exposure to MLOps / LLMOps practices
• Knowledge of API integrations and microservices architecture
• Experience in enterprise AI deployments (banking, risk, or financial services preferred)
• Contributions to open-source AI/LLM projects
• Familiarity with agent evaluation benchmarks and guardrails