{"id":2774982,"url":"https://alion.io/job/ltm-senior-data-scientist-7","title":"Senior Data Scientist","company":{"id":9353,"name":"Ltm","domain":"ltm.com","url":"https://alion.io/company/ltm","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"RippleHire","truth_index":{"grade":"B","score":81,"open_postings":163,"ghost_share":0,"stale_share":0.773,"repost_share":0,"time_to_fill_p50_days":52,"computed_at":"2026-10-17T05:46:00Z"}},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Kolkata, 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engineering teams product stakeholders and delivery teams to develop AInative solutions using LLM based reasoning multiagent orchestration RAG patterns vector search prompt management AI evaluation observability and secure deployment practices\nKey Responsibilities\nLead the design and implementation of AIfirst and agentic AI solutions for the\nstrategic modernization\nBuild and integrate LLMbased reasoning capabilities into claim and\noperational workflows to improve efficiency and reduce manual effort\nDesign and implement multiagent orchestration patterns using enterprisestandard\nAI frameworks\nDevelop scalable Pythonbased AI services APIs MCP servers and\nautomation components\nImplement RAGbased solutions using embeddings vector stores and\nenterprise knowledge sources\nCreate and manage versioncontrolled prompts using prompt management\npractices\nEstablish AI quality validation through response evaluation grounding checks\nand output testing\nEnsure AI security controls including PII detection guardrails and prompt\ninjection defense\nCollaborate with engineering architecture product and delivery teams to\nconvert AI concepts into productionready capabilities\nProvide technical leadership to developers and engineers working on AInative\nuse cases\nSupport CICD infrastructure automation observability and productionreadiness\npractices\nPartner with stakeholders during technical screening solution walkthroughs\nand onboarding into PI delivery cycles\nRequired Technical Skills\nAI Agentic AI\nStrong handson experience in LLM application development\nAgentic AI design and implementation experience\nMultiagent orchestration experience\nPrompt engineering and prompt lifecycle management\nAI evaluation and response quality validation\nExperience with secure AI design including guardrails and PII handling\nPreferred AI Stack Alignment\nAWS Bedrock\nAgentCore\nClaude Sonnet\nAWS Strands SDK\nAmazon Titan Embeddings v2\nBedrock Prompt Management\nBedrock Guardrails\nAgentCore Evals Braintrust\nEngineering Platform Skills\nStrong programming expertise in Python\nExperience building APIs using FastAPI\nKnowledge of TypeScript and React for AIenabled UI integration\nExperience with GitHub and GitHub Actions\nInfrastructure automation exposure using Terraform or AWS CDK\nExperience with observability and tracing using OpenTelemetry\nFamiliarity with monitoring AI agents for latency token cost execution steps and\nreliability\nWorking knowledge of Dynatrace ELK and OTel is preferred\nFunctional Domain Expectations\nAbility to understand claim lifecycle workflows and identify AI automation\nopportunities\nExperience translating business problems into AIenabled workflow solutions\nAbility to support modernization initiatives across assisted surfaced and\nautomated AI maturity phases\nStrong understanding of enterprisegrade delivery expectations not just\nprototype development\nAbility to work in SAFe PIbased delivery environments\nModernization objectives include integrating LLMbased reasoning into claim\nprofessional workflows automating repetitive claim tasks using multiagent\norchestration delivering productiongrade agentic AI and building a durable AI delivery\nmodel that scales across the value stream\nMandatory Qualifications\n8 years of software engineering experience\n3 years of handson AI ML LLM engineering experience\nStrong Python development background\nPractical experience with LLMbased application architecture\nExperience building APIs automation services or AInative backend services\nExperience with cloudnative AI services preferably AWS\nStrong understanding of RAG embeddings vector search and prompt\nmanagement\nExperience with CICD Gitbased development and production deployment\npractices\nStrong communication skills and ability to work with distributed 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