AI Product Engineer

Job Overview

As an AI Product Engineer at BDIPlus, you will be responsible for designing, developing, and delivering scalable enterprise software products that incorporate modern AI capabilities.

This is a hands-on product development role requiring extensive full stack engineering experience, strong system design skills, and the ability to build products from architecture through production. You will work across the full technology stack, developing user-facing functionality, backend services, APIs, data integrations, and platform components while incorporating AI capabilities such as agents, agentic workflows, RAG, LLM pipelines, embeddings, and vector search where they add value to the product.

You will work closely with Product, Engineering, Data Science, and Infrastructure teams to translate product requirements into well-designed, scalable software solutions.

We are looking for an engineer who thinks beyond individual AI use cases. The ideal candidate understands how to build products, make sound architectural decisions, develop across the full stack, and integrate AI and agentic capabilities into reliable enterprise software.

What You’ll Do

Product Development & Full Stack Engineering

• Design, develop, and deliver enterprise software products and product features end-to-end.
• Take ownership of product development from technical design and architecture through implementation, testing, deployment, and ongoing enhancement.
• Build modern front-end experiences, backend services, APIs, data integrations, and platform components.
• Translate product requirements and user needs into scalable technical solutions.
• Develop reusable services and components that support multiple product capabilities and workflows.
• Work closely with Product teams to evaluate requirements, technical feasibility, tradeoffs, and implementation approaches.
• Apply strong software engineering practices including modular architecture, automated testing, CI/CD, code reviews, and secure development.

System Design & Architecture

• Own and contribute to system design and technical architecture for new products, features, and platform capabilities.
• Design scalable, distributed systems that support enterprise workloads.
• Define service boundaries, APIs, data flows, integration patterns, and application architecture.
• Make architectural decisions considering scalability, latency, resiliency, security, maintainability, observability, and cost.
• Design systems capable of integrating traditional application logic, enterprise data, and AI-driven functionality.
• Clearly document architecture decisions and technical tradeoffs.

Agents & Agentic Workflows

• Design and implement AI agents and agentic workflows as integrated capabilities within BDIPlus products.
• Build stateful, multi-step workflows using LangGraph and related orchestration frameworks.
• Implement tool calling, routing, memory, state management, human-in-the-loop processes, and workflow orchestration.
• Enable agents to securely interact with APIs, databases, enterprise systems, and product services.
• Determine when agentic approaches are appropriate versus deterministic workflows and traditional application logic.
• Design agent workflows with appropriate controls, monitoring, fallbacks, and error handling for production environments.

RAG, LLM & Retrieval Pipelines

• Design and implement RAG and LLM pipelines that support product functionality.
• Build ingestion and processing pipelines for structured and unstructured enterprise information.
• Implement document processing, chunking, metadata enrichment, embeddings/vector embeddings, indexing, and retrieval.
• Design and optimize semantic search, vector search, keyword search, and hybrid search.
• Implement filtering, re-ranking, query rewriting, context optimization, and retrieval evaluation.
• Integrate LLMs and retrieval capabilities into broader application and product workflows.
• Implement grounding, citations, validation, and hallucination-mitigation techniques.
• Build permission-aware retrieval aligned with enterprise access controls and entitlements.

Product Quality & Production Engineering

• Build software that is secure, scalable, testable, observable, and production-ready.
• Establish automated testing and evaluation across traditional software components and AI-powered functionality.
• Monitor application performance, latency, errors, token usage…