Top Remote Platform Engineer Jobs in Chicago, IL

Automate cloud infrastructure as code, build developer tooling, administer Kubernetes and platform services, improve CI/CD and observability, collaborate with product teams, run on-call rotation and manage incident runbooks to ensure platform reliability and developer productivity.

Build and scale AI platform infrastructure for internal agents across AWS/GCP. Integrate identity (Okta, OAuth2/OIDC), implement agentic security, containerized deployments (Docker/Kubernetes), CI/CD and Terraform-based pipelines, run vendor evaluations, and design observability/telemetry for LLM-driven workflows while collaborating with security, identity, and engineering teams.

Build the core AI platform and high-performance Rust backend powering an AI-native trading copilot. Implement streaming responses, low-latency tool execution, caching, orchestration of models and tools, secure APIs, auditing/tracing, and safe, auditable trading action infrastructure. Partner with product and frontend to enable AI-native UX and translate trading domain requirements into resilient platform primitives.

The engineer will build and operate AI/ML infrastructure, managing services on AWS and bare metal, using tools like Kubernetes and Terraform.

Own and evolve the data infrastructure powering identity and fraud products. Build and operate scalable ETL/ELT pipelines, ensure data quality and observability, optimize storage and access, support product squads, respond to production incidents, mentor engineers, and drive data platform innovation.

Lead the Data Platform Engineering team owning ETL/reverse-ETL pipelines, replication, and production datastores. Define architecture, roadmap, standards (IaC, observability, schema contracts), mentor engineers, drive incident response and durable fixes, and partner on cross-team technical decisions and operational reliability for data correctness, completeness, and timeliness.

Senior Windows-focused Platform Engineer responsible for administering Windows server environments, supporting IBM FileNet/DataCap/BAW/ICN applications, ensuring security and performance, implementing monitoring, troubleshooting production issues, documenting systems, and collaborating with internal teams and clients to improve platform stability and processes.

Lead operational reliability and platform enablement for Databricks: build monitoring, CI/CD, deployment standards, compute and job policies, observability, runbooks, and governance to support secure, cost-aware, production data workloads across regulated environments. Mentor engineers and align platform with cloud/infrastructure and compliance requirements.

Own and operate the Microsoft Fabric and Power BI platform end-to-end: administer tenants, capacities, OneLake, and governance; build secure data integration pipelines and access layers for BI and AI agents; automate CI/CD and platform operations; enforce security and data governance; and translate business requirements into technical designs while liaising between IT, security, and business stakeholders.

As a Senior Software Engineer, you will design best practices for AI Agents, develop standards, collaborate on product opportunities, and stay updated on emerging Agent techniques.

Design, build, and operate enterprise-scale multi-cloud infrastructure (Azure primary, GCP, AWS exposure). Own landing zones, Terraform modules, production AKS/GKE Kubernetes, Vault secrets, hybrid networking, CI/CD pipelines, monitoring, DR, and automation (Ansible, Python/Bash). Mentor engineers, document runbooks, and collaborate with security, application teams, and leadership to ensure secure, reliable, cost-optimized cloud platforms.

Responsible for the full software development lifecycle, collaborating with teams to design, develop, and maintain applications while mentoring others and ensuring engineering standards.

Lead and set technical strategy for the Order Platform powering post-checkout flows (orders, captures, refunds, settlement). Design and ship highly available backend systems, own reliability/operational practices, mentor engineers, collaborate cross-functionally, and drive long-term technical decisions and execution plans.

Lead technical vision and implement high-impact Ruby on Rails solutions for an internal demo platform. Improve reliability, observability, instrumentation, and integrations; partner with Product, Sales, and cross-functional teams; mentor engineers and drive architecture, testing, and engineering best practices.

Design, build, and operate internal developer platforms, CI/CD pipelines, developer environments, deployment workflows, and shared services. Create automation and custom tooling, prototype and productionize AI-assisted engineering workflows, strengthen cloud and container foundations (Kubernetes, IaC), instrument platforms with telemetry, and own platform projects end-to-end including rollout, adoption, and on-call.

Lead design, build, and deploy of large-scale data platforms for LLMs, RAG, and agentic AI systems. Hands-on coding, architecting fault-tolerant pipelines, establishing MLOps/DataOps best practices, mentoring engineers, and operationalizing research into production across Exabyte-scale distributed systems.

Design, implement, and maintain scalable hybrid multi-cloud Kubernetes platforms at massive scale. Ensure high reliability, integrate open-source observability tools, provide technical direction, operate large Linux environments across cloud and data centers, handle on-call duties, and mentor junior engineers.

As a Staff Software Engineer, you will enhance platform engineering by improving deployment strategies and developer experiences, establishing reliable systems and mentorship across teams.

Build and maintain scalable, governed data pipelines from ingestion through transformation and integration. Implement schema validation, data quality checks, job monitoring, and production-grade APIs. Work with Python, SQL, Airflow, dbt, AWS (EMR, Athena, S3), Iceberg/Parquet, and contribute to CI/CD, observability, and on-call support while collaborating with analytics and product teams.

Lead technical strategy and architecture for Coinbase's Blockchain Platform, overseeing nodes, indexers, wallets, and asset lifecycle. Drive cross-team platform rearchitectures, enforce security and reliability standards, champion AI-driven automation, use observability to improve reliability, and represent the platform to executives to secure alignment and resources for large-scale blockchain infrastructure initiatives.

Lead technical design and implementation of the ISPM product using Ruby on Rails. Build scalable data pipelines and systems to process large-scale identity telemetry, collaborate with security researchers and product teams, mentor engineers, and set architectural direction for detection and remediation features.

Build and lead development of the ESPM platform using Ruby on Rails. Define technical vision, design scalable data pipelines and architectures for petabyte-scale ingestion, implement features across the stack, collaborate with security researchers, mentor engineers, and ensure high-quality, tested deliveries.

Lead design and implementation of Affirm's Lakehouse Platform using Iceberg, Spark, Snowflake, and cloud storage. Drive platform roadmap, governance, access controls, performance and cost optimization, analytics engineering best practices, observability, and on-call readiness. Partner cross-functionally, mentor engineers, and build scalable, secure, self-service data infrastructure and semantic/agentic data tools.

Build and operate ML training and serving infrastructure; design, develop, and launch backend systems; collaborate across teams to decompose projects; maintain availability through monitoring and on-call support; review and debug large codebases; contribute to hiring and team growth.

Design, build, and operate low-latency authentication and authorization services (OAuth, sessions, tokens, 2FA, account recovery). Lead technical designs, ensure strong security and observability, collaborate cross-functionally, simplify integrations, and mentor engineers while running production services with measurable SLOs.