Agentic Engineer

* Requires minimum of 2 days a week onsite in Boston, MA office

Base salary range: $135,000 to $170,000 USD, plus annual bonus. Final compensation will be determined based on experience, skills, qualifications, and relevant market data.

IANS is rapidly expanding its AI strategy toward a Data-as-a-Service (DaaS) model, delivering not only insights through our own applications, but also structured data feeds, APIs, and AI ready interfaces that enable clients to build their own intelligent systems and agentic workflows.

We are seeking an Agentic Engineer to build and ship the agent capabilities at the heart of IANS' agentic AI platform. This is a hands‑on builder's role: working within the platform architecture set by our senior and principal engineers, you will implement, test, and operate the agents, tools, retrieval components, and evaluation suites that power both our internal AI products and the client‑facing agent platform that consumes IANS data feeds.

You will own well-scoped features end‑to‑end — from design through production — and grow your scope as you demonstrate ownership and judgment.

This is an exceptional opportunity to do serious agentic engineering early in your career: you will work daily with engineers who have shipped production multi‑agent systems, on a platform where evaluation, observability, and security are first‑class concerns rather than afterthoughts.

• Build, test, and ship production-quality agent capabilities — tools, retrieval components, memory features, orchestration steps, and evaluation coverage — within the platform's established architecture.
• Implement agent and tool-use patterns with frameworks such as Lang Chain, Lang Graph, Llama Index, Auto Gen, or comparable systems, with regression coverage and observability included in every change.
• Integrate retrieval-augmented generation (RAG), structured tool use, MCP-style tool protocols, and APIs into robust, enterprise-grade platform components.
• Contribute to the developer-facing primitives that allow external clients to safely extend the IANS agent platform with their own proprietary data and workflows.

• Extend benchmarking, regression testing, and observability suites that measure agent quality, latency, cost, reliability, and safety, using modern AI observability tooling such as Lang Smith, Langfuse, Arize, or Weights & Biases.
• Write and maintain evaluations for agentic behaviors — tool-use correctness, hallucination rates, multi-turn coherence, and task completion — for the features you ship.
• Investigate eval regressions and production incidents in agent behavior, and land the fixes.
• Participate actively in design reviews and code reviews, absorbing and applying feedback from senior and principal engineers.
• Take progressively larger ownership as you build a track record, from features to subsystems.
• Stay current on the rapidly evolving agentic AI landscape (frontier models, orchestration frameworks, evaluation standards, agent protocols) and share what you learn with the team.

• Ship production code across the stack:
  Go for services and agent runtimes, Python for AI/ML workflows, and React with Type Script for customer-facing and internal web applications.
• Build the APIs and microservices that internal teams and external clients use to integrate with IANS' data and agent platforms.
• Test, log, trace, and performance-tune everything you ship, including agent workflows and model-driven systems.

• Deploy and operate services on IANS' AWS-based agent infrastructure, including AWS ECS agent runtimes, AWS Bedrock for foundation model access, and AWS Lambda for tool execution.
• Contribute to the data pipelines, vector databases, and retrieval systems that support RAG, agent memory, embeddings, and inference at scale.
• Instrument token usage, latency, and inference cost for the features you own.

• Follow IANS' standards for security, data isolation, governance, observability, and cost control in everything you ship, especially where agent…