Indiana Staffing
Senior AI Platform Engineer
This role requires associates to be in-office 1 - 2 days per week, fostering collaboration and connectivity, while providing flexibility to support productivity and work-life balance. This approach combines structured office engagement with the autonomy of virtual work, promoting a dynamic and adaptable workplace. Alternate locations may be considered if candidates reside within a commuting distance from an office. Please note that per our policy on hybrid/virtual work, candidates not within a reasonable commuting distance from the posting location(s) will not be considered for employment, unless an accommodation is granted as required by law. The Senior AI Platform Engineer will design, build, and operate production AI systems that power platform experiences: RAG pipelines, model endpoints, evaluation harnesses, guardrails, and multi tenant AI services published through a developer hub/marketplace. How You Will Make an Impact
Lead end to end AI solutioning: problem framing, data sourcing, labeling strategy, model/LLM selection, and safety considerations. Build retrieval augmented generation and agentic workflows: document processing, chunking/embedding strategies, vector indexing, prompt/chain design, tool use, and guardrails (content filters, policy enforcement). Implement evaluation with golden datasets, automatic metrics, rubric based grading, and human in the loop reviews; run A/B and interleaving tests. Productionize inference (synchronous, batch, streaming) with autoscaling, caching, request routing/fallbacks, cost and token/latency budgets, and kill switch patterns. Establish LLMOps/MLOps foundations: experiment tracking, model registry, data/model lineage, governance, CI/CD for models/prompts, and safe rollback. Instrument AI observability (prompt traces, quality drift, hallucination/safety events, per tenant cost dashboards); drive continual improvement cycles. Partner with platform engineers to expose AI capabilities as APIs/SDKs, publish to the marketplace with metadata, versioning, and deprecation policies. Collaborate with security, privacy, and risk on data minimization, access controls, PII handling, and policy aligned evaluation, document tradeoffs and decisions. Mentor engineers and data scientists; create reusable evaluation harnesses, prompt libraries, and templates that accelerate feature delivery. Minimum Requirements: Requires a Bachelor's degree in a highly quantitative field (Computer Science, Machine Learning, Operational Research, Statistics, Mathematics, etc.) or equivalent degree and 6 or more years of experience; or any combination of education and experience in configuration management, which would provide an equivalent background. Preferred Skills, Capabilities & Experiences: Strong Python plus one systems language; experience with model serving (batch/online), GPU utilization, and optimization (quantization, distillation). Practical knowledge of vector databases, embedding generation, prompt/chain orchestration, and evaluation methodologies for generative systems. Experience integrating with feature stores, catalogs/registries, and data governance controls in cloud environments. Familiarity with responsible AI topics (safety, privacy, bias) and how to operationalize them in production. For candidates working in person or virtually in the below location(s), the salary range for this specific position is $152,680 to $249,840. Locations: California, Illinois and Washington. In addition to your salary, Elevance Health offers benefits such as, a comprehensive benefits package, incentive and recognition programs, equity stock purchase and 401k contribution (all benefits are subject to eligibility requirements). The salary offered for this specific position is based on a number of legitimate, non-discriminatory factors set by the Company. The Company is fully committed to ensuring equal pay opportunities for equal work regardless of gender, race, or any other category protected by federal, state, and local pay equity laws.
This role requires associates to be in-office 1 - 2 days per week, fostering collaboration and connectivity, while providing flexibility to support productivity and work-life balance. This approach combines structured office engagement with the autonomy of virtual work, promoting a dynamic and adaptable workplace. Alternate locations may be considered if candidates reside within a commuting distance from an office. Please note that per our policy on hybrid/virtual work, candidates not within a reasonable commuting distance from the posting location(s) will not be considered for employment, unless an accommodation is granted as required by law. The Senior AI Platform Engineer will design, build, and operate production AI systems that power platform experiences: RAG pipelines, model endpoints, evaluation harnesses, guardrails, and multi tenant AI services published through a developer hub/marketplace. How You Will Make an Impact
Lead end to end AI solutioning: problem framing, data sourcing, labeling strategy, model/LLM selection, and safety considerations. Build retrieval augmented generation and agentic workflows: document processing, chunking/embedding strategies, vector indexing, prompt/chain design, tool use, and guardrails (content filters, policy enforcement). Implement evaluation with golden datasets, automatic metrics, rubric based grading, and human in the loop reviews; run A/B and interleaving tests. Productionize inference (synchronous, batch, streaming) with autoscaling, caching, request routing/fallbacks, cost and token/latency budgets, and kill switch patterns. Establish LLMOps/MLOps foundations: experiment tracking, model registry, data/model lineage, governance, CI/CD for models/prompts, and safe rollback. Instrument AI observability (prompt traces, quality drift, hallucination/safety events, per tenant cost dashboards); drive continual improvement cycles. Partner with platform engineers to expose AI capabilities as APIs/SDKs, publish to the marketplace with metadata, versioning, and deprecation policies. Collaborate with security, privacy, and risk on data minimization, access controls, PII handling, and policy aligned evaluation, document tradeoffs and decisions. Mentor engineers and data scientists; create reusable evaluation harnesses, prompt libraries, and templates that accelerate feature delivery. Minimum Requirements: Requires a Bachelor's degree in a highly quantitative field (Computer Science, Machine Learning, Operational Research, Statistics, Mathematics, etc.) or equivalent degree and 6 or more years of experience; or any combination of education and experience in configuration management, which would provide an equivalent background. Preferred Skills, Capabilities & Experiences: Strong Python plus one systems language; experience with model serving (batch/online), GPU utilization, and optimization (quantization, distillation). Practical knowledge of vector databases, embedding generation, prompt/chain orchestration, and evaluation methodologies for generative systems. Experience integrating with feature stores, catalogs/registries, and data governance controls in cloud environments. Familiarity with responsible AI topics (safety, privacy, bias) and how to operationalize them in production. For candidates working in person or virtually in the below location(s), the salary range for this specific position is $152,680 to $249,840. Locations: California, Illinois and Washington. In addition to your salary, Elevance Health offers benefits such as, a comprehensive benefits package, incentive and recognition programs, equity stock purchase and 401k contribution (all benefits are subject to eligibility requirements). The salary offered for this specific position is based on a number of legitimate, non-discriminatory factors set by the Company. The Company is fully committed to ensuring equal pay opportunities for equal work regardless of gender, race, or any other category protected by federal, state, and local pay equity laws.