AI Engineer

Beacon Hill; United States; Remote; USD 180,000 - 250,000; Full time

Job summary

Beacon Hill is seeking an experienced senior software engineer to leverage generative AI to design, build, and scale AI-driven applications on Azure platforms. You will blend hands-on architecture with coaching, mentor onshore and offshore teams, and lead client‑facing execution.

The role emphasizes publishing production‑grade LLM-powered solutions, agentic workflows, and secure, cloud‑native designs using Azure, Docker, and Kubernetes in an agile setting.

Qualifications

• 10+ years of full stack software engineering experience.
• SME across an organization’s AI tools and services.
• Design, develop, deploy, and maintain enterprise AI applications, including conversational interfaces, knowledge graphs, and RAG workflows.
• Use AI-native development for coding, testing, debugging, and documentation while validating generated artifacts.
• Strong Python and React experience with SQL and APIs.
• Experience with GitHub Copilot and coding assistants is ideal.
• Experience with Azure AI Foundry, Azure OpenAI, Azure AI Search, and Azure Document Intelligence is ideal.
• Prompt engineering, document ingestion/extraction, RAG, tool integration, and multi-step agentic workflows.
• Evaluation of datasets, prompt regression testing, tracing, and quality/safety measurement is ideal.
• Familiarity with Foundry Evaluators, RAGAS, or similar approaches is ideal.

Responsibilities

• Design, build, and scale AI-driven applications delivering measurable business outcomes.
• Provide technical leadership and mentor engineers across onshore and offshore teams.
• Collaborate with IT and business stakeholders to translate requirements into AI-enabled solutions.
• Deliver production‑grade LLM-powered experiences including chat, document intelligence, and agentic workflows.

Skills

Full stack engineering

AI tools SME

Python

React

SQL & APIs

GitHub Copilot

Azure AI

RAG & agentic workflows

Prompt engineering

Security & auth

CI/CD & IaC

Docker & Kubernetes

REST APIs

Tools

Azure OpenAI

Azure AI Foundry

Azure AI Search

Azure Document Intelligence

Git

Terraform

Docker

Kubernetes

LangGraph

Semantic Kernel

DSPy

GitHub Copilot

Job description

This is a great opportunity for an experienced senior-level software engineer to use their experience with generative AI to design, build, and scale AI‑driven applications that deliver measurable business outcomes. This role is a blend of hands‑on architecture, development, coaching and mentoring, technical leadership, client‑facing execution, and a strong emphasis on Azure‑based AI platforms, LLM integrations, and agentic systems for fast AI experimentation pilots. If you are a software engineering professional who is on the leading edge of AI and building efficiency, this is a great opportunity.

Required Skills:

• Must have 10+ years’ experience in full stack software engineering
• Must be able to serve as a SMEacross an organization’s AI tools and services
• Must be able to design, develop, deploy, and maintain enterprise AI applications, including conversational interfaces, knowledge graphs, retrieval-augmented generation (RAG), and agentic workflows
• Must be able to use AI-native development for coding, testing, debugging, and documentation while independently validating generated artifacts and maintaining engineering standards
• Must have strong Python and React experience as well as experience with SQL, API’s and modern application architecture
• Experience with use of GitHub Copilot and approved coding assistants, including repository context, test generation, code review, debugging, and validation of generated implementations is ideal
• Experience with Azure AI Foundry, Azure OpenAI, Azure AI Search, and Azure Document Intelligence is ideal along with practical experience integrating model services into applications
• Must have experience with prompt engineering, document ingestion/extraction, RAG, tool integration, and multi-step agentic workflows
• Must have experience with evaluating datasets, prompt regression testing, tracing, and quality/safety measurement is ideal
• Familiarity with Foundry Evaluators, RAGAS, or comparable approaches is ideal
• Experience with Azure, Azure Functions, Git, CI/CD, infrastructure as code/Terraform, containers/Docker, and Agile delivery practices is ideal
• Experience with REST APIs, identity/access controls, OAuth/JWT or Entra-based authentication, and secure data handling is ideal
• Must have experience delivering multiple AI use cases into production at scale
• Must have a solid understanding and experience with generative AI in the software development space
• Must be able to architect and deliver production‑grade LLM‑powered applications, including chat, document intelligence, and agentic workflows
• Must be able to mentor onshore and offshore engineering teams on use of AI to improve code quality, architecture discipline, and delivery velocity
• Must be able to design scalable, secure, cloud‑native systems using Azure, Docker, Kubernetes, and event‑driven architectures
• Experience with agent frameworks such as LangGraph, Semantic Kernel, or DSPy, and agent tracing/evaluation tools is a plus
• Must be able to design and implement prompt engineering, evaluation frameworks, and observabilityfor AI systems
• Must be able to ensure enterprise standards for authentication, authorization, and system integration
• Must be able to collaborate on requirements gathering, solution design, and development with other IT app dev and business stakeholders
• Must be able to translate business problems into AI‑enabled and agentic solutions
• Must be able to design systems capable of processing high‑volume documents and transactionswith accuracy and traceability
• Must be able to continuously iterate solutions based on real‑world usage and feedback
• Must be a self‑starter who can work independently but also with a team with little oversite
• Must be able communicate with various IT teams as well as business stakeholders on occasion