{"id":1285786,"url":"https://alion.io/job/1stobject-senior-aiml-engineer","title":"Senior AI/ML Engineer","company":{"id":3802042,"name":"1Stobject","domain":"1stobject.com","url":"https://alion.io/company/1stobject","size_band":null,"is_staffing_agency":true,"employer_type":"agency","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":null,"work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"inferred_company_offices","remote_working_hours":null,"hiring_geo_confidence":"inferred","locations":["Bengaluru, India","Noida, India"],"countries":["IN"],"hiring_countries":["IN"],"hiring_countries_total":1,"salary":null,"salary_estimate":{"min_usd":39000,"max_usd":99000,"period":"year","method":"role_seniority_country_cell","sample_n":10},"experience_years_min":6,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"A2A","optional":false},{"name":"Anthropic","optional":false},{"name":"AutoGen","optional":false},{"name":"Azure","optional":false},{"name":"Azure DevOps","optional":false},{"name":"CI/CD","optional":false},{"name":"Claude","optional":false},{"name":"CrewAI","optional":false},{"name":"Docker","optional":false},{"name":"FAISS","optional":false},{"name":"FastAPI","optional":false},{"name":"Function Calling","optional":false},{"name":"Gemini","optional":false},{"name":"Google ADK","optional":false},{"name":"Human-in-the-Loop","optional":false},{"name":"Kubernetes","optional":false},{"name":"LangChain","optional":false},{"name":"Langfuse","optional":false},{"name":"LangGraph","optional":false},{"name":"LLM","optional":false},{"name":"LLM Evaluation","optional":false},{"name":"LLM Guardrails","optional":false},{"name":"Mistral","optional":false},{"name":"Model Context Protocol","optional":false},{"name":"OpenAI","optional":false},{"name":"pgvector","optional":false},{"name":"Pinecone","optional":false},{"name":"PostgreSQL","optional":false},{"name":"Python","optional":false},{"name":"Qdrant","optional":false},{"name":"RAG","optional":false},{"name":"Semantic Kernel","optional":false},{"name":"Structured Outputs","optional":false},{"name":"Tool Use","optional":false},{"name":"Weaviate","optional":false},{"name":"AI Agents","optional":true},{"name":"Federated Learning","optional":true},{"name":"Fine-tuning","optional":true},{"name":"GDPR","optional":true}],"status":"live","first_seen_at":"2026-08-12T06:00:45Z","employer_posted_date":null,"last_verified_at":"2026-08-12T06:00:45Z","board_verified":false,"closed_at":null,"days_open":46,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":46},"description":"Hiring : Senior AI/ML Engineer\n\nExperience : 6+ Years\n\nLocation : Bangalore & Noida\n\nMode of Work : Hybrid\n\nSummary : \n\nWe are looking for a Senior AI/ML Engineer to join an Agent Development Squad building AI-powered financial close automation. You will own the LLM and agent layer, designing and building agent workflows using LangChain/LangGraph, integrating with Azure OpenAI or other frontier LLMs, and ensuring every agent action is traceable, evaluable, and production-grade. This is a hands-on engineering role, not a research role. The platform is Python-first, and you will work alongside backend and frontend engineers in a cross-functional squad.\n\nWhat You'll Do : \n\n- Design and build LLM-based agent workflows using LangChain and LangGraph, covering multi-step graphs, tool use, agent handoffs, and state management.\n\n- Integrate and optimize Azure OpenAI or other frontier LLM providers (Anthropic Claude, Google Gemini, etc.), managing prompt design, token usage, latency, and model versioning.\n\n- Build and maintain RAG pipelines covering document ingestion, embedding generation, vector search using pgvector or equivalent vector database, and retrieval-augmented generation for financial document reasoning.\n\n- Own LLM observability using Langfuse, instrument agent traces, build evaluation harnesses, track confidence scores, and detect model regressions.\n\n- Collaborate with the Software Engineering Architect on agent orchestration patterns and inter-agent communication contracts.\n\n- Contribute to confidence threshold calibration, defining the auto-resolve vs. human-escalation boundary per agent.\n\n- Ensure all agent actions produce structured, auditable outputs compatible with the platform's SOX-compliant governance framework.\n\nWho You Are : \n\nAI / LLM Engineering - Primary Gate : \n\n- 6+ years of total software engineering experience with 3+ years building and shipping production-grade LLM-based applications.\n\n- Proven experience building production-grade agents, both assistive (human-in-the-loop, approval-driven) and ambient (autonomous, background execution), using LangChain, LangGraph, and LangServe; knows when to use each and how they compose.\n\n- Familiarity with agent communication protocols, specifically Model Context Protocol (MCP) and Agent-to-Agent (A2A) and working knowledge of other Agent Development Kits such as Google ADK, AutoGen, CrewAI, or Semantic Kernel.\n\n- Experience integrating with Azure OpenAI or other frontier LLM provider APIs (Anthropic Claude, Google Gemini, Mistral, etc.), including structured outputs, function calling, token management, and latency optimization.\n\n- RAG pipeline development with hands-on experience in at least one vector database (pgvector, Pinecone, Weaviate, Qdrant, FAISS, or equivalent), covering embedding pipelines and retrieval strategies.\n\n- Prompt lifecycle management and eval pipelines, covering versioning, rollback, environment-specific configuration, and running evaluation harnesses to regression-test prompt changes and validate RAG output.\n\n- Experience building reliable production agent systems with input/output guardrails, confidence thresholding, fallback handling, and full traceability of every decision and tool call via Langfuse or equivalent.\n\nBackend Engineering : \n\n- Python is your primary language; proficient with FastAPI or equivalent async frameworks for building agent service APIs.\n\n- PostgreSQL with pgvector or equivalent vector database (Pinecone, Weaviate, Qdrant, FAISS), including schema design for agent state, audit logs, and vector search.\n\n- Docker and Kubernetes for containerized service deployment in production environments.\n\n- Azure DevOps CI/CD for integrating AI pipelines into automated build and deployment workflows.\n\nNice to Have : \n\n- Experience with financial domain data such as accounting entries, reconciliations, accruals, or variance analysis.\n\n- Familiarity with SOX/GDPR compliance requirements for AI decision audit trails.\n\n- Contributions to open-source LLM or agent framework projects.\n\n- Experience with federated learning or model fine-tuning pipelines.\n\nWhat You'll Learn & Gain : \n\n- End-to-end ownership of the LLM and agent layer on a live enterprise financial platform used by global customers.\n\n- Deep hands-on experience with LangChain/LangGraph, Azure OpenAI and other frontier LLMs, agent protocols (MCP, A2A), and Langfuse in a production context where quality, auditability, and latency all matter.\n\n- Exposure to building AI in a high-compliance, SOX-governed environment, balancing model performance with explainability and audit requirements.\n\n- Collaboration with backend, frontend, and platform engineers in a squad model where your technical decisions directly shape product behavior.\n\nSkills\nMachine Learning, Python, Artificial Intelligence, LangChain, LLM, FastAPI, VectorDB, LangGraph, OpenAI, Agentic AI","description_format":"text","description_chars":4887,"description_truncated":false,"requirements":{"experience_years_min":6,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[{"name":"India","iso":"IN","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":[],"lifecycle":[{"event":"open","at":"2026-09-26T04:00:00Z"}],"liveness":{"score":6,"band":"cold","label":"Long shot","p_open":0.4,"p_active":0.342,"p_room":0.45,"age_days":45,"expected_fill_days":30,"reasons":["seen:45","agency","velocity","win:tail"],"computed_at":"2026-09-27T05:45:00Z"},"pay":null,"html_url":"https://alion.io/job/1stobject-senior-aiml-engineer","json_url":"https://alion.io/job/1stobject-senior-aiml-engineer.json","meta":{"generated_at":"2026-09-28T02:39:44Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","usage":{"tier":"crawler","counted_by":"address","units_charged":1,"used_today":1392,"day_limit":5000,"remaining_today":3608,"minute_limit":60,"resets_at":"2026-09-29T00:00:00Z"}}}