{"id":3145481,"url":"https://alion.io/job/ltm-senior-specialist-ai-engineering-3","title":"Senior Specialist - AI Engineering","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":77,"open_postings":174,"ghost_share":0,"stale_share":0.937,"repost_share":0,"time_to_fill_p50_days":41,"computed_at":"2026-10-26T05:57:25Z"}},"role":"AI/ML","role_family":"AI/ML","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":["Bengaluru, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":23000,"max_usd":48000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":41},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Amazon SageMaker","optional":false},{"name":"AWS","optional":false},{"name":"AWS Bedrock","optional":false},{"name":"Embeddings","optional":false},{"name":"Hallucination","optional":false}],"status":"live","first_seen_at":"2026-10-22T00:00:00Z","employer_posted_date":"2026-10-23","last_verified_at":"2026-10-26T15:30:40Z","board_verified":true,"closed_at":null,"days_open":4,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":4},"description":"Roles &Responsibilities:\nRCA Agent Development\nDesign develop and enhance the RCA agent using GenAIagentic AI patterns\nBuild prompts reasoning workflows toolfunction integrations and supporting APIs\nOptimize agent accuracy reliability latency safety and cost\nAD RCA Integration\nIntegrate the upstream AD workflow with the RCA agent through enterprise APIsservice layers\nImplement data and workflow integration between the agent and dependent enterprise systems\nValidate endtoend integration and errorhandling scenarios\nEvaluation Framework\nBuild an automated evaluation frameworktest harness for the RCA solution\nDefine acceptance criteria and metrics covering accuracy factuality grounding safety latency and cost\nPerform regression adversarial hallucination guardrail and failurepath testing\nUse evaluation findings as release gates and inputs for system improvement\nE2E Tuning Optimization\nAnalyze failures across the complete RCA pipeline and tune prompts context orchestration and inference behavior\nImprove accuracy and production reliability based on evaluation results\nIdentify error propagation across multistep agent workflows through tracing and observability\nAWS SageMaker Bedrock\nDevelop and operationalize agent workloads using Amazon Bedrock where applicable\nSupport model deployment optimization monitoring and lifecycle activities using SageMaker\nOptimize prompts embeddings and inference performance\nEstablish monitoring for production performance and anomalies\nShort version for JD RR\nKey Responsibilities\nDevelop and enhance the RCA agent integrate ADtoRCA workflows build the GenAI evaluation framework perform endtoend testing and tuning optimize promptsmodel inference and support deployment monitoring and operationalization using AWS SageMaker and Amazon Bedrock","description_format":"text","description_chars":1787,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Artificial 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