Senior Engineer, Agent Harness Engineering

Intellectsoft

. Design and build core agent harnesses covering function calling, tool interfaces, context assembly, retrieval integration, subagent delegation, retry logic, and failure handling .

Posted 10/28/2026full-timeBengaluru • IndiaSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and deploying LLM-based systems, with strong proficiency in Python and experience in operationalizing AI applications. Capable of translating client requirements into effective agent architectures while ensuring robust evaluation and monitoring processes.

Highest-signal resume keywords

Python ProgrammingLLM-Based Systems DevelopmentDeployment of User-Facing AI ApplicationsAPI Design and IntegrationContainerization and Cloud Services

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Hard Skills

PythonLLM APIsAsyncioPydanticPytestCI/CDAPI DesignData EvaluationOrchestration FrameworksVersion Control

Soft Skills

Strong Communication SkillsStakeholder EngagementAdaptability to Project Priorities

Tools & Technologies

LangfusePydantic LogfireLangGraphOpenAI Agents SDKMCP ServersInfrastructure as Code

Industry Keywords

Healthcare Data StandardsCDISCSNOMEDMedDRAGxP21 CFR Part 11HIPAAGDPR

Tech Stack

Tools & technologies

AssemblyCloudPythonSQL

About the role

Key responsibilities & impact

Design and build core agent harnesses covering function calling, tool interfaces, context assembly, retrieval integration, subagent delegation, retry logic, and failure handling
Take agentic systems from initial concept to scalable production, managing deployment, monitoring, cost, latency, and operational support against live enterprise client data
Build and maintain evaluation suites, task benchmarks, scoring rubrics, and regression tests using tools such as Langfuse, Pydantic Logfire, or custom SDKs
Integrate client enterprise systems, data sources, and internal APIs as accessible agent tools
Build and manage Model Context Protocol (MCP) servers
Translate ambiguous client requirements into robust agent architectures and advise stakeholders on whether an agentic pattern is appropriate
Interface directly with client stakeholders and articulate technical trade-offs to non-technical audiences
Contribute reusable harness components to shared internal tooling
Document design decisions to meet audit, validation, and handover standards

Requirements

What you’ll need

2–3 years of professional software engineering experience, including substantive work building LLM-based or agentic systems (beyond prompt-level experimentation)
Proven track record of deploying user-facing AI applications to production, including operational experience with monitoring, versioning, rate limiting, cost control, and incident response
Strong Python skills with production-grade test coverage, typing, asyncio, Pydantic, Pytest, packaging, version control, CI/CD, and robust API design
Hands-on experience with LLM APIs, function/tool calling, structured outputs, streaming, and context window management
Experience building or extending orchestration frameworks such as LangGraph, deepagents, OpenAI Agents SDK, or custom harnesses
Ability to define success criteria, design evaluation datasets, and systematically evaluate non-deterministic AI outputs
Working knowledge of containerization and at least one major cloud provider to ship and maintain services independently
Strong written and verbal communication skills with the ability to represent technical positions credibly and thrive amid shifting project priorities
Nice to have: prior exposure to healthcare, pharma, or biotech data and standards including CDISC, SNOMED, and MedDRA
Nice to have: familiarity with GxP, 21 CFR Part 11, HIPAA, GDPR, audit logging, and formal system validation
Nice to have: experience with LLM tracing tools or developing and hosting MCP servers
Nice to have: experience with RAG pipelines, vector search, fine-tuning, distillation, or model serving
Nice to have: Infrastructure as Code, CI/CD, large-scale data processing, and advanced SQL experience
Nice to have: consulting/client services experience, agentic developer tooling, or open-source contributions/publications

Benefits

Comp & perks

Employment-based cooperation
Comprehensive insurance for you and your family (health, life, and accident)
Paid PTO policy (vacation, sick leaves, and public holidays)
Tech equipment provided
Udemy courses, workshops, trainings & expert knowledge-sharing
Flexible hours & work setup