AI Agent Engineer

Insight Global; Burlington (MA); On-site; USD 150,000 - 210,000; Full time

Job summary

Insight Global is seeking an experienced Agentic AI Engineer to lead design, development, and deployment of GenAI-powered solutions. You will architect multi-agent systems, integrate LLMs, and drive production deployments with a focus on reliability, security, and cost efficiency.

You will partner with business stakeholders to translate requirements into scalable AI solutions and roadmaps, mentoring teams on agent design, prompt engineering, and model optimization.

Qualifications

• Bachelor's degree in Computer Science, Engineering, Data Science, AI, or related field.
• 10+ years technology experience with 5+ years AI engineering platforms in healthcare/biotech.
• Experience developing GenAI solutions in Life Sciences.
• Strong expertise with agentic AI frameworks (LangChain, LangGraph, CrewAI, AutoGen, Haystack, AutoGPT, BabyAGI, CAMEL, MetaGPT).
• Advanced Python skills; prompt engineering, tool integration, agent orchestration, vector DBs, RAG pipelines, memory architectures.
• Experience with leading LLMs (GPT-4, Claude, Gemini, etc.).
• Proven cloud-native AI deployment on AWS/Azure/GCP.
• Leadership in complex AI initiatives from PoC to production.
• Experience with model performance optimization, scalability, cost management.
• Knowledge of AI governance, privacy, and responsible AI practices.
• Regulated Life Sciences/pharma/biotech experience.

Responsibilities

• Architect agentic AI solutions using orchestration frameworks.
• Design multi-agent architectures including planner-solver, hierarchical agents.
• Define GenAI architectures: model selection, memory, tools, observability, security.
• Build reusable AI tooling, APIs, and memory architectures.
• Lead AI-powered assistants, copilots, and automation platforms.
• Evaluate and optimize commercial and open-source LLMs and RAG solutions.
• Improve performance, reliability, cost efficiency while ensuring compliance.
• Establish GenAIOps and LLMOps best practices (monitoring, logging, testing).
• Mentor teams on agent design, prompt engineering, optimization.
• Collaborate with product/business to map requirements to scalable AI solutions.
• Stay current with multi-agent systems and GenAI advancements.

Skills

Python programming

Prompt engineering

Agent orchestration

LLM integration

RAG pipelines

Memory architectures

Tool integration

Vector databases

Model optimization

Cloud platforms

Education

Bachelor's degree in CS/Engineering/Data Science/AI

Tools

LangChain

LangGraph

CrewAI

AutoGen

Haystack

AutoGPT

BabyAGI

CAMEL

MetaGPT

Job description

Job Description

Insight Global is seeking an experienced Agentic AI Engineer to lead the design, development, and deployment of advanced AI solutions leveraging large language models (LLMs), multi‑agent systems, and modern GenAI frameworks. This individual will play a key role in architecting scalable AI applications, driving innovation, and partnering with business stakeholders to deliver intelligent automation and decision‑support solutions.

Responsibilities:

• Architect and implement agentic AI solutions using modern orchestration frameworks such as LangChain, LangGraph, CrewAI, AutoGen, and similar technologies.
• Design and develop multi‑agent architectures including planner‑solver frameworks, hierarchical agents, autonomous agent teams, and goal decomposition workflows.
• Define end‑to‑end GenAI architectures encompassing model selection, orchestration, memory management, tool integrations, observability, security, and deployment strategies.
• Build reusable AI tooling, APIs, and memory architectures that support scalable and efficient agent interactions.
• Lead development and production deployment of AI‑powered assistants, copilots, workflow automation platforms, and decision‑support applications.
• Evaluate, integrate, and optimize commercial and open‑source LLMs, multimodal AI models, and Retrieval‑Augmented Generation (RAG) solutions.
• Improve system performance, reliability, scalability, and cost efficiency while ensuring adherence to responsible AI, security, privacy, and compliance standards.
• Establish GenAIOps and LLMOps best practices, including monitoring, evaluation, logging, testing, and continuous improvement processes.
• Mentor engineering teams on agent design patterns, prompt engineering, model optimization, and AI implementation best practices.
• Collaborate with product, business, and technical stakeholders to translate requirements into scalable AI solutions and strategic roadmaps.
• Stay current with advancements in multi‑agent systems, cognitive architectures, and emerging AI technologies

We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances.

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Skills and Requirements

• Bachelor's degree in Computer Science, Engineering, Data Science, Artificial Intelligence, or a related field.
• 10+ years of overall technology experience, including 5+ years supporting AI engineering platforms in the healthcare, biotechnology
• Experience developing domain‑specific GenAI solutions within Life Sciences environments.
• Strong expertise with agentic AI frameworks including LangChain, LangGraph, CrewAI, AutoGen, Haystack, AutoGPT, BabyAGI, CAMEL, and MetaGPT.
• Advanced Python programming skills and experience with prompt engineering, tool integration, agent orchestration, vector databases, RAG pipelines, and memory architectures.
• Experience working with leading LLMs such as GPT-4, Claude, Gemini, Mistral, and other commercial or open‑source models.
• Proven experience designing, deploying, and managing cloud‑native AI solutions on AWS, Azure, and/or Google Cloud Platform.
• Strong architecture and technical leadership experience with a track record of delivering complex AI initiatives from proof of concept through production deployment.
• Experience with model performance optimization, scalability planning, cost management, and operational support of AI systems. Experience with reinforcement learning, agent simulation, or environment modeling.
• Knowledge of AI governance, regulatory compliance, privacy requirements, and responsible AI practices within enterprise environments.
• Prior experience supporting regulated Life Sciences, pharmaceutical, or biotechnology organizations.