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Agentic AI Lead

Sutherland

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What agentic roles keep asking for: LLMs (31%), Python (28%), AWS (25%), Observability (22%), Generative AI (17%), RAG (17%), System design (14%) — counted across their open postings here.

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  1. Why do you want to join Sutherland?
  2. What is your experience with AWS? Tell me one thing you learned the hard way.
  3. Tell me about a time the data was messy or wrong. What did you do?
  4. How would you explain your model's result to someone who is not technical?
  5. What would you check first if a model's accuracy dropped after going live?

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Builds and deploys AI agents that execute regulated and semi-regulated processes on AWS Bedrock, and owns the document-processing pipelines that feed structured data into those agent workflows — replacing manual steps without introducing RPA-style brittle automation. Key Responsibilities Agent Development: Build agents on Bedrock (Amazon Nova and other foundation models) for document generation, data validation, and case intake use cases. Implement Fargate task logic following established service patterns (e.g., mail-triggered tasks, chatbot-triggered tasks). Integrate with Microsoft Graph API for Teams-based delivery (message consumption, file attachment handling, callback delivery of outputs). Write and maintain prompt/agent configurations with appropriate guardrails for regulated activity (e.g., escalation to a human reviewer for non-standard cases). Unit- and integration-test agent outputs against defined accuracy/turnaround-time KPIs. Work within a distributed delivery model — code and configuration must be portable across sites. Document Processing: Deploy and maintain a document-processing Fargate service (chatbot-triggered document processing, output report delivery via callback). Integrate third-party extraction tooling into the environment as an early-milestone deliverable ahead of full go-live. Build extraction pipelines for structured and semi-structured documents across varying quality/formats. Collaborate with the QA/compliance function to ensure extracted data supports audit trail requirements. Tune extraction accuracy against baseline KPIs before handover to production agent workflows. Required Experience 8+ years software engineering experience, with 3+ years building LLM-based applications (prompt engineering, RAG, agent orchestration frameworks). Working knowledge of AWS Bedrock APIs, Python, and event-driven service patterns (SQS/SNS consumers). 4+ years’ experience in document processing/OCR/IDP (Intelligent Document Processing) roles, including hands-on work with AWS Textract or equivalent, plus Azure Document Intelligence. Experience with financial services or regulated documents preferred. Domain process exposure is a differentiator, not a requirement — training will be provided via SOP handover.

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Listed on smartrecruiters · posted 2026-09-02. ApplySarthi collects openings and links to application pages; the role is advertised by Sutherland, not by us.