{"id":2260455,"url":"https://alion.io/job/astrazeneca-senior-cloud-platform-engineer-aws-ai-infrastructure-evinova-2","title":"Senior Cloud Platform Engineer (AWS), AI Infrastructure - Evinova","company":{"id":13195,"name":"AstraZeneca","domain":"astrazeneca.com","url":"https://alion.io/company/astra-zeneca","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"A","score":94,"open_postings":198,"ghost_share":0,"stale_share":0.429,"repost_share":0.051,"time_to_fill_p50_days":14,"computed_at":"2026-10-20T05:45:00Z"}},"role":"DevOps","role_family":"DevOps","seniority":"senior","employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Gaithersburg, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":145000,"max":185000,"currency":"USD","period":"year","gross":null,"usd_annual":185000},"salary_estimate":null,"experience_years_min":4,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"AIOps","optional":false},{"name":"Amazon CloudWatch","optional":false},{"name":"Amazon ECS","optional":false},{"name":"Amazon EKS","optional":false},{"name":"Amazon S3","optional":false},{"name":"Amazon SageMaker","optional":false},{"name":"Anthropic","optional":false},{"name":"AWS","optional":false},{"name":"AWS Bedrock","optional":false},{"name":"AWS Bedrock AgentCore","optional":false},{"name":"AWS CDK","optional":false},{"name":"CI/CD","optional":false},{"name":"Datadog","optional":false},{"name":"Docker","optional":false},{"name":"Gemini","optional":false},{"name":"GitOps","optional":false},{"name":"IAM","optional":false},{"name":"Langfuse","optional":false},{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"OpenAI","optional":false},{"name":"OpenTelemetry","optional":false},{"name":"Platform Engineering","optional":false},{"name":"Prometheus","optional":false},{"name":"Pydantic","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"SLI/SLO/SLA","optional":false},{"name":"Splunk","optional":false},{"name":"SRE","optional":false},{"name":"Terraform","optional":false},{"name":"TypeScript","optional":false},{"name":"Vertex AI","optional":false},{"name":"Arize Phoenix","optional":true},{"name":"Braintrust","optional":true},{"name":"Kubernetes","optional":true},{"name":"Model Context Protocol","optional":true},{"name":"Multi-Agent Systems","optional":true}],"status":"live","first_seen_at":"2026-10-01T00:00:00Z","employer_posted_date":"2026-10-01","last_verified_at":"2026-10-20T19:06:43Z","board_verified":true,"closed_at":null,"days_open":19,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":19},"description":"WHY JOIN US?\nEvinova is a health-tech business focused on accelerating better health outcomes by advancing digital transformation across the life sciences sector. By combining science-based expertise, evidence-led rigor, and deep human insight, we design digital solutions that enable healthcare to work better for everyone.\nOperating at the intersection of healthcare, technology, data, and analytics, we are helping unlock the full potential of digital health, transforming how clinical research is conducted, how care is delivered, and how patients experience healthcare. Our solutions are built to scale, driving efficiency, improving decision-making, and ultimately delivering better outcomes for patients worldwide.\nAt Evinova, we are driven by a shared purpose to transform health through data and digital innovation. Our teams collaborate across disciplines to solve complex challenges, continuously learning and evolving in a fast-paced, high-impact environment.\nWe also recognize the importance of flexibility and balance. Our ways of working support both individual needs and team collaboration. To foster connection and collaboration, employees are expected to work from the office three days per week, creating opportunities for in-person teamwork, innovation, and meaningful connection.\nThis role is located in Gaithersburg, Maryland and follows a hybrid work model. Candidates must reside within commuting distance of Gaithersburg or be willing to relocate for this opportunity.\nIntroduction to Role\nThe Machine Learning and Artificial Intelligence Operations team (ML/AI Ops) is the cloud platform engineering team responsible for building and operating the infrastructure that enables our AI Engineers and Data Scientists to deploy Generative AI applications reliably, securely, efficiently and at scale.\nAs a Senior Cloud Platform Engineer on the ML/AI Ops team, you will design, build and operate the AWS platform that runs our production Generative AI, agentic AI and conversational AI workloads. Most of the code you write will be AWS CDK (TypeScript and/or Python) that creates the infrastructure for other teams to build on.\nThis is a cloud and platform engineering role rather than an AI application development role. You will partner closely with the engineers and Data Scientists who build agents and models, and provide the infrastructure, deployment patterns, model access, observability and operational capabilities they need to move solutions from experimentation into reliable production environments.\nYou will work across AWS infrastructure, infrastructure as code (IaC), Amazon Bedrock AgentCore, Amazon ECS, CI/CD, SageMaker Unified Studio, AI gateways, observability, scalability, reliability, security, governance and cost optimization. Your work will establish reusable platform capabilities that allow teams across Evinova to deploy and operate solutions faster and more reliably while meeting the requirements of a highly regulated pharmaceutical environment.\nAccountabilities\nCloud Platform Engineering\nDesign, build and operate scalable AWS cloud platform capabilities for production ML/AI and Generative AI workloads.\nCreate reusable infrastructure, tooling and deployment patterns that enable AI Engineers and Data Scientists to independently deploy and operate their applications.\nWrite and maintain AWS IaC primarily AWS CDK in TypeScript and/or Python, including reusable CDK constructs that other teams consume.\nBuild and operate containerized workloads using Amazon ECS and AgentCore.\nDevelop reusable platform capabilities across compute, networking, IAM, secrets management, storage, model access and workload isolation.\nBuild and maintain CI/CD and GitOps workflows that enable safe, automated and repeatable deployments across environments.\nPartner with engineers and Data Scientists to transition prototypes and research workloads into resilient, production-grade services.\nBuild self-service capabilities and automation that improve developer experience and reduce operational toil.\nReliability, Scalability & Operational Excellence\nEngineer platform capabilities that improve the availability, scalability, resiliency and performance of production GenAI workloads.\nDesign and implement autoscaling, load balancing, retries, timeouts, fallback, rate limiting and failure-recovery strategies.\nEstablish monitoring, alerting, SLOs, runbooks and production-readiness standards for ML/AI workloads.\nTroubleshoot complex production issues across AWS infrastructure, container, application and model-provider layers.\nAutomate operational processes and proactively identify opportunities to improve platform reliability and performance.\nDrive cloud and model cost optimization through capacity management, workload optimization and data-driven analysis.\nAI Gateway & Model Access\nBuild and operate a centralized AI gateway that routes requests across model providers.\nProvide secure, reliable and governed access to foundation models through Amazon Bedrock, OpenAI, Anthropic, Microsoft Foundry, Gemini Enterprise Agent Platform (formerly Vertex AI) and other model platforms.\nImplement model/provider routing, fallback, authentication, rate limiting, quotas and cost controls.\nEnable AI teams to evaluate and change model providers without tightly coupling their applications to individual model endpoints.\nProvide the compute, networking, storage and runtime infrastructure to reliably operate agentic AI, RAG and conversational AI workloads in production.\nObservability, Governance & Cost Optimization\nBuild platform-level observability for GenAI workloads, including token consumption, latency, throughput, errors, model/provider performance and cost attribution by team and application.\nImplement standardized tracing, logging, metrics and alerting capabilities that can be adopted across AI applications.\nIntegrate observability technologies such as Amazon CloudWatch, OpenTelemetry, Datadog and Splunk.\nBuild the telemetry and data pipelines that AI teams use to evaluate and monitor production LLM behavior.\nBuild appropriate security, auditability and governance controls for AI workloads operating within a regulated environment.\nSupport compliance with applicable industry standards and practices, including Good Clinical Practice and Good Machine Learning Practice and other GxP related standards and practices.\nRepresentative Projects\nBuild a library of AWS CDK constructs that gives an AI team a production-ready Amazon ECS service, with IAM, secrets, networking and observability, from a single import.\nDeploy and operate a centralized AI gateway on Amazon ECS, with multi-provider routing, fallback, quotas and rate limiting.\nBuild multi-account CI/CD with CDK Pipelines or GitOps, with safe, staged deployments across environments.\nImplement token cost attribution by team and application with SLO and burn-rate alerts.\nMigrate container workloads from Amazon EKS to Amazon ECS without loss of reliability.\nEssential Skills/Experience\nMinimum of 4 years of hands-on experience in a platform engineering, infrastructure, site reliability engineering (SRE) or DevOps role where infrastructure code was your main output.\nDeep hands-on AWS cloud engineering experience, including designing, deploying and operating production cloud-native infrastructure.\nStrong experience with AWS services such as Bedrock, ECS, IAM, VPC, load balancing, S3, CloudWatch, Secrets Manager and related services.\nStrong hands-on experience with IaC. AWS CDK using Python and/or TypeScript is preferred. Strong Terraform engineers who are willing to work in CDK are welcome.\nStrong experience with Docker and Amazon ECS, including workload deployment, autoscaling, resource management, health checks, networking, security and production troubleshooting.\nExperience designing and maintaining CI/CD and/or GitOps pipelines for production cloud workloads.\nStrong understanding of cloud and platform engineering principles, including high availability, scalability, resiliency, observability, performance, security and cost optimization.\nExperience with on-call rotations, incident response and root-cause analysis for production systems.\nStrong software engineering skills in Python and/or TypeScript, with experience building production-quality platform tooling and automation.\nExperience implementing production observability using technologies such as CloudWatch, OpenTelemetry, Prometheus, Splunk, Datadog, Pydantic Logfire, Langfuse or comparable tools.\nDemonstrated experience partnering with software, data or ML/AI teams to transition workloads from experimentation into reliable production environments.\nProven ability to collaborate effectively across ML/AI engineering, software engineering, security, infrastructure and product teams.\nStrong written and verbal communication skills, including the ability to clearly document infrastructure architecture, operational processes and platform standards.\nPreferred Skills/Experience\nExperience building internal developer platforms or self-service cloud capabilities used by multiple engineering teams.\nExperience supporting Generative AI/LLM workloads in production, with an understanding of their unique operational challenges including model availability, latency, token consumption, evaluation and cost.\nHands-on experience with Amazon Bedrock or another enterprise foundation-model platform.\nExperience implementing and/or configuring AI/model gateways, proxies or routing layers, including model routing, fallback, rate limiting and provider abstraction.\nExperience operating infrastructure supporting agentic AI, multi-agent systems, RAG pipelines or conversational AI.\nExperience with AgentCore or comparable managed agent-runtime capabilities.\nExperience supporting Model Context Protocol (MCP) tools, servers or services.\nExperience with LLM evaluation and observability platforms such as Arize Phoenix, Langfuse, Braintrust, Freeplay or Logfire.\nExperience supporting production ML/AI infrastructure within pharmaceutical, healthcare, financial services or another highly regulated industry.\nUnderstanding of GxP and/or other controls applicable to regulated ML/AI systems.\nExperience with Kubernetes (Amazon EKS), including migrating container workloads to Amazon ECS.\nThis Role Is Not a Good Fit If\nYour main experience is building agents, RAG pipelines, prompts or LLM applications, and you have not owned production infrastructure.\nYou have not written or maintained infrastructure as code for production systems.\nYou prefer research or model development to operating production platforms.\nPersonal Attributes\nPlatform-minded: You think beyond individual applications and build reusable capabilities that enable multiple engineering teams.\nOperationally focused: You care about reliability, scalability, observability, security, performance and what happens after a workload reaches production.\nHands-on: You are comfortable writing code, building infrastructure, operating container platforms and troubleshooting production systems.\nCustomer-obsessed: You view the AI Engineers and Data Scientists using the platform as your customers and continually look for ways to improve their developer experience.\nOrganized and attentive to detail: You effectively manage multiple initiatives and competing priorities.\nCollaborative and inclusive: You foster a positive engineering culture where teams share knowledge and solve problems together.\nComfortable working autonomously: You like working in an evolving environment where you can help establish new systems, patterns, and best practices.\nCurious and committed to staying current: You love learning and applying that knowledge to the systems you build. You stay current with the latest AI trends and technologies and apply that knowledge to your work pragmatically.\nSO, WHAT’S NEXT?\nTo be considered for this exciting opportunity, please complete the full application on our website at your earliest convenience - it is the only way that our R...","description_format":"text","description_chars":14337,"description_truncated":true,"requirements":{"experience_years_min":4,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":["Equity","Hybrid work","Retirement plans"],"hiring_locations":[{"name":"United States","iso":"US","kind":"country"}],"hiring_excludes":[],"relocation_offered":true,"industries":["Prescription Drugs","Oncology Therapeutics","Rare Disease Therapeutics","Cardiometabolic Therapeutics"],"lifecycle":[{"event":"open","at":"2026-10-11T05:06:20Z"}],"visa":[],"liveness":{"score":40,"band":"fade","label":"Fading","p_open":1,"p_active":0.722,"p_room":0.55,"age_days":19,"expected_fill_days":14,"reasons":["conf:1","velocity","win:tail","comp:brand"],"computed_at":"2026-10-20T05:45:00Z"},"pay":{"stated_usd_annual":185000,"is_top_pay":true},"html_url":"https://alion.io/job/astrazeneca-senior-cloud-platform-engineer-aws-ai-infrastructure-evinova-2","json_url":"https://alion.io/job/astrazeneca-senior-cloud-platform-engineer-aws-ai-infrastructure-evinova-2.json","meta":{"generated_at":"2026-10-20T20:43:47Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","about":"Alion is a live layer of people, companies and AI agents: who they are, whether they are real and active right now, what they do and how to work with them, readable by people and by agents and paid per call.","catalog":"https://alion.io/catalog.json","usage":{"tier":"crawler_verified","counted_by":"address","units_charged":1,"used_today":24084,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-10-21T00:00:00Z"}},"offers":[{"id":"company.slices","title":"One company in depth, by slice","status":"live","price":{"credits":0.02,"usd":0.002,"plus_per_slice":{"credits":0.05,"usd":0.005}},"unit":"per company, plus each slice with data","note":"the employer in depth","call":{"mcp_tool":"get_company","arguments":{"id":13195},"rest":"https://alion.io/mcp/rest/get_company?id=13195"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fastrazeneca-senior-cloud-platform-engineer-aws-ai-infrastructure-evinova-2"},{"id":"market.stats","title":"A market slice: pay, demand and time to fill","status":"live","price":{"credits":1,"usd":0.1},"unit":"per slice","note":"pay, demand and time to fill for this role and place","call":{"mcp_tool":"market_stats"},"human":"https://alion.io/catalog?offer=market.stats&for=job%2Fastrazeneca-senior-cloud-platform-engineer-aws-ai-infrastructure-evinova-2"},{"id":"job.search","title":"Open jobs by role, technology, place, pay and visa","status":"live","price":{"credits":0.02,"usd":0.002},"unit":"per posting in a list","note":"similar open postings","call":{"mcp_tool":"search_jobs"},"human":"https://alion.io/catalog?offer=job.search&for=job%2Fastrazeneca-senior-cloud-platform-engineer-aws-ai-infrastructure-evinova-2"},{"id":"company.verify","title":"Is this company real and active right now","status":"pilot","price":null,"unit":"per company","request":{"url":"https://alion.io/catalog/request","method":"POST","body":"{\"offer\": \"company.verify\", \"for\": \"job/astrazeneca-senior-cloud-platform-engineer-aws-ai-infrastructure-evinova-2\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fastrazeneca-senior-cloud-platform-engineer-aws-ai-infrastructure-evinova-2"}]}