Senior AI Engineer

Job Description: Senior AI Engineer — Multi-Agent Platform Company Name: DATA CONTAINERS CONSULTING PRIVATE LIMITED Job Title / Role: Senior AI Engineer Type of Employment: Full Time & C2C Experience Required: 3–9 years Number of Positions: 6 CTC: 30–60 LPA Work Location: Bangalore (Preference given to Bangalore - Kothanur) Mode of Work: Remote Notice Period / Start Date: 0–30 days (Serving Notice Period only) About the Project & Role We are building a multi-agent orchestration platform for enterprise document and transaction processing. The technical core is durable orchestration—long-running workflows that pause for human approval for hours or days, recover from tool failures, and replan without losing state. Agents read unstructured documents, classify against complex taxonomies, and write into legacy systems through typed connectors spanning mainframe terminal emulation, EDI, and JDBC. Key Responsibilities & What You'll Do • Build and own sub-agents: typed input/output schemas, versioned prompts, a constrained tool set, and a published success metric for each. • Design the orchestration layer — planning, replanning, tool-failure recovery, and handoff between supervisor and sub-agents. • Build the eval harness that decides when an agent is safe to promote from shadow to assisted to autonomous. • Work the two-tier model setup: a heavy model for judgment and classification, a lighter self-hosted tier for high-volume extraction and formatting. • Make agent behaviour observable and debuggable — traces, cost per agent, failure attribution. Must-Have Qualifications & Requirements • Production Experience: You've shipped LLM systems into production, not just demos. You can talk about what broke and what you changed. • Orchestration: Comfortable with agent orchestration in some form — LangGraph, custom runtimes, workflow engines, or your own. We care more about the reasoning than the library. • Programming Languages: Strong Python. Go or TypeScript useful. • Evaluation: You've built evals, or you've felt the pain of not having them. • Reliability: Solid on structured output, schema validation, and getting reliable behaviour out of unreliable models. Good-to-Have Skills • Durable execution experience — Temporal, Cadence, Step Functions, or similar. • Self-hosted inference: vLLM, TGI, quantisation, GPU scheduling. • Retrieval systems at scale, and knowing when not to use them. • Document understanding: OCR, layout parsing, extraction from messy PDFs. • Anything regulated — audit trails, approval workflows, compliance reporting. Interview Process & Logistics • Interview Rounds: 1. L1 - Assessment Q&A 2. L2 - Tech 3. HR • Office Timings: 9:30 AM to 6:30 PM (Applicable as per standard operational guidelines)