Careers

Agent Engineer

Build and harden agents in the stable: skills, tools, guardrails, escalation rules, and the evaluation that proves a change before it ships.

Objective

We're looking for an Agent Engineer to design, build, and harden AI agents in production. You'll own the full agent lifecycle — from skills and tool integrations to guardrails, escalation logic, and the evaluation harness that proves every change is safe to ship.

About the role

As an Agent Engineer at Zentis you'll design, build, and harden AI agents in production. You'll own the full agent lifecycle — from skills and tool integrations to guardrails, escalation logic, and the evaluation harness that proves every change is safe to ship.

You'll work at the intersection of deterministic systems and language models: most regulated BFSI work is narrow and well-specified, so your job is to make agents behave predictably — writing deterministic rules that run before any model does, wiring tools to systems of record, and turning "seems right" into a number the whole team can defend to a compliance audience.

This is a senior individual-contributor role with real ownership. You are not implementing tickets; you are deciding how a class of work gets done safely, and defending that decision in writing to the rest of the team.

Key responsibilities

Design and implement autonomous/semi-autonomous AI agents with well-defined skills and tools
Build guardrails, safety layers, and escalation rules for high-stakes workflows
Develop and maintain evaluation frameworks (offline + online) for agent behavior
Optimize agent reliability, latency, and cost across production workloads
Collaborate with ML, Platform, and Solutions teams to ship agent capabilities end-to-end
Debug complex multi-step agent failures and continuously improve robustness

Required skills

3+ years in software/ML engineering with strong Python proficiency
Hands-on experience with LLM frameworks (LangChain, LlamaIndex, LangGraph, CrewAI, or similar)
Experience building with agentic patterns — tool use, ReAct, planning, memory
Solid understanding of prompt engineering, RAG, and function calling
Familiarity with LLM evaluation (RAGAS, DeepEval, custom harnesses)
Experience with vector databases (Pinecone, Weaviate, Qdrant, pgvector)
Strong grasp of API design, async programming, and distributed systems

Nice to have

Experience with observability tools (LangSmith, Langfuse, Arize)
Background in BFSI, compliance, or regulated environments
Contributions to open-source agent frameworks

Skills & technologies

PythonLLM frameworksAgentic patternsPrompt engineeringRAGFunction callingLLM evaluationVector databasesDistributed systems

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About the role

Key responsibilities

Design and implement autonomous/semi-autonomous AI agents with well-defined skills and tools

Build guardrails, safety layers, and escalation rules for high-stakes workflows

Develop and maintain evaluation frameworks (offline + online) for agent behavior

Optimize agent reliability, latency, and cost across production workloads

Collaborate with ML, Platform, and Solutions teams to ship agent capabilities end-to-end

Debug complex multi-step agent failures and continuously improve robustness

Required skills

3+ years in software/ML engineering with strong Python proficiency

Hands-on experience with LLM frameworks (LangChain, LlamaIndex, LangGraph, CrewAI, or similar)

Experience building with agentic patterns — tool use, ReAct, planning, memory

Solid understanding of prompt engineering, RAG, and function calling

Familiarity with LLM evaluation (RAGAS, DeepEval, custom harnesses)

Experience with vector databases (Pinecone, Weaviate, Qdrant, pgvector)

Strong grasp of API design, async programming, and distributed systems

Agent Engineer

Objective

About the role

Key responsibilities

Required skills

Nice to have

Skills & technologies

Role at a glance

Rather talk than apply?

Agent Engineer

Objective

About the role

Key responsibilities

Required skills

Nice to have

Skills & technologies

Role at a glance

Rather talk than apply?