IANS
Agentic Engineer
Boston, MA
Sponsorship not specified$135k-$170kDetected 17 hours ago
TypeScriptPythonJavaGoRustC#ReactCode ReviewVector DatabasesAWSCloud PlatformsMachine LearningData EngineeringLLMsRAGAgentic AILangGraphAI OrchestrationCybersecurityIncident ResponseComplianceManual TestingResearchCommunication
About the role
- *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.
Responsibilities
- Contribute to the developer-facing primitives that allow external clients to safely extend the IANS agent platform with their own proprietary data and workflows.
- Write and maintain evaluations for agentic behaviors - tool-use correctness, hallucination rates, multi-turn coherence, and task completion - for the features you ship.
- 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.
- Build the APIs and microservices that internal teams and external clients use to integrate with IANS' data and agent platforms.
- 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.
- Implement access controls, sandboxing, and audit logging requirements in the components you build.
- Build in compliance with regulatory frameworks (GDPR, CCPA, etc.) and IANS' SOC 2 Type II controls, and uphold responsible AI practices.
- We are seeking an Agentic Engineer to build and ship the agent capabilities at the heart of IANS' agentic AI platform.
Requirements
- Proficiency in Go, or strong proficiency in a comparable systems language (Rust, TypeScript, Java, C#) with the ability to become productive in Go quickly
- working knowledge of Python for AI/ML workflows.
- Familiarity with cloud infrastructure, ideally AWS (ECS, Lambda, Bedrock, or comparable services).
- Required
- 3-5 years of software engineering experience, including hands-on work building LLM powered features or agentic systems that reached production users.
- Experience building web applications with React (or a comparable modern frontend framework) and TypeScript.
- Experience building and shipping LLM-powered applications - whether with an agent framework such as LangChain, LangGraph, LlamaIndex, or AutoGen, or directly against model APIs. Strong engineering fundamentals matter more to us than any particular.
- Working understanding of RAG, embeddings, vector databases, and prompt/context.
- Strong testing and debugging discipline, and the habit of instrumenting what you ship.
- Clear written and verbal communication and a demonstrated appetite for feedback and growth.
Nice to have
- Exposure to AI evaluation and observability tooling such as LangSmith, Langfuse, Arize, or Weights & Biases.
- Experience with MCP-style tool protocols or building tools for AI agents.
- Experience operating services in production (on-call, incident response, performance tuning).
- Familiarity with fine-tuning or post-training techniques (LoRA, PEFT, RLHF, DPO).
- Contributions to open-source AI or agent tooling.
- Cybersecurity domain familiarity.
- Agentic engineering is a young discipline, and few candidates will check every box above.
Compensation
- $135,000 to $170,000 USD, plus annual bonus.
- Final compensation will be determined based on experience, skills, qualifications, and relevant market data.
Benefits
- 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 LangChain, LangGraph, LlamaIndex, AutoGen, or comparable systems, with regression coverage and observability included in every change.
This listing is sourced directly from IANS's careers page and normalized into a canonical job model.