{"id":2068243,"url":"https://alion.io/job/pathnovo-ai-harness-engineer","title":"AI Harness Engineer","company":{"id":3832899,"name":"Pathnovo","domain":"pathnovo.com","url":"https://alion.io/company/pathnovo","size_band":"11-50","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":"middle","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Bengaluru, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":22000,"max_usd":52000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":25},"experience_years_min":3,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"Arize Phoenix","optional":false},{"name":"Braintrust","optional":false},{"name":"DeepEval","optional":false},{"name":"Embeddings","optional":false},{"name":"Function Calling","optional":false},{"name":"Knowledge Graph","optional":false},{"name":"Langfuse","optional":false},{"name":"LangSmith","optional":false},{"name":"LLM","optional":false},{"name":"Multi-Agent Systems","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"Ragas","optional":false},{"name":"Tool Use","optional":false},{"name":"TypeScript","optional":false}],"status":"live","first_seen_at":"2026-10-08T05:03:28Z","employer_posted_date":null,"last_verified_at":"2026-10-08T05:03:28Z","board_verified":false,"closed_at":null,"days_open":5,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":5},"description":"We are looking for an AI Harness Engineer who can build and scale production-grade AI systems and the infrastructure that makes AI agents reliable, observable, and effective in real-world applications. This role is ideal for someone with a strong backend and distributed systems foundation who has moved beyond experimentation into applied AI/genAI product development. You should have hands-on experience building AI products, multi-agent systems, LLM evaluation frameworks, and production AI workflows.\nResponsibilities:\nBuild and scale production-grade AI systems and AI-powered products from 01 and beyond.\nDesign robust backend services and distributed systems supporting AI/agentic workloads.\nBuild AI harnesses, evaluation frameworks, and testing infrastructure to measure LLM and agent performance.\nDevelop and evaluate multi-agent workflows, tool-use systems, and agent orchestration.\nWork with LLMs, GenAI, RAG, agentic AI, and applied AI systems in production.\nDesign systems for LLM evaluation, observability, reliability, latency, and quality measurement.\nBuild and work with graph databases for knowledge representation, relationships, agent memory, and reasoning workflows.\nDevelop backend components and AI infrastructure primarily using Python and TypeScript.\nDesign systems capable of handling scale, concurrency, fault tolerance, retries, and distributed execution.\nCollaborate closely with product and engineering teams to convert AI capabilities into real customer-facing products.\nContinuously improve AI systems through experimentation, evaluation, feedback loops, and production metrics.\nRequirements:\nWe are looking for an engineer who is not just an LLM API integrator.\nThe ideal candidate has a strong software engineering foundation and has actually built, shipped, and operated an AI product in production.\nYou should be comfortable working across the stack, from distributed backend systems and data infrastructure to LLM evaluation, agent orchestration, and production AI reliability.\nMust-Have Skills:\n3-5.5 years of software engineering experience.\nStrong backend engineering experience with distributed systems.\nStrong hands-on experience with Python and TypeScript.\nProduction experience building GenAI / applied AI systems.\nStrong understanding of LLM evaluation and AI quality measurement.\nExperience building multi-agent systems / agentic AI workflows.\nExperience with graph databases and graph-based architectures.\nExperience building and operating production AI systems, not just prototypes or POCs.\nStrong understanding of APIs, microservices, databases, asynchronous processing, and distributed architectures.\nExperience building an AI-powered product end-to-end is highly preferred.\nStrongly Preferred:\nExperience working at a Series A or Series B startup, particularly in a high-ownership engineering environment.\nExperience taking an AI product from 01 to production.\nExperience with LLM providers, RAG, embeddings, vector databases, tool calling, and agent orchestration.\nFamiliarity with AI evaluation tools/frameworks such as LangSmith, Langfuse, Braintrust, Arize/Phoenix, Ragas, DeepEval, or equivalent.\nExperience with agent memory, knowledge graphs, graph-based retrieval, or reasoning systems.\nExperience building AI systems with strong observability, tracing, evaluation, 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now","p_open":1,"p_active":0.903,"p_room":1,"age_days":5,"expected_fill_days":30,"reasons":["seen:5","velocity","win:early"],"computed_at":"2026-10-13T05:45:00Z"},"pay":null,"html_url":"https://alion.io/job/pathnovo-ai-harness-engineer","json_url":"https://alion.io/job/pathnovo-ai-harness-engineer.json","meta":{"generated_at":"2026-10-13T12:29:05Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","about":"Alion is a live layer of people, companies and AI agents: who they are, whether they are real and active right now, what they do and how to work with them, readable by people and by agents and paid per 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