Senior AI focused AWS DevOps Engineer

We are lookong for Senior AI focused AWS DevOps Engineer.

Forma spolupráce

Freelance, TPP

Nasazení

Remote

Umístění

Praha (CZ)

Mzda

from 270€/MD

Mám zájem o tuto pozici

Náplň práce

We’re hiring a senior engineer to lead AI-focused application development while owning cloud infrastructure and deployments on AWS. You’ll design and build core product features in TypeScript and Python, provision resources using AWS CDK or similar tooling, troubleshoot complex deployment issues, and work directly with client Cloud Engineering teams to align on requirements, architecture, and operational best practices.

What you’ll do:

Design, build, and ship AI-powered services and integrations using Python and TypeScript.
Define and provision AWS infrastructure using AWS CDK or equivalent (e.g., CDKTF, SST, Pulumi); implement reusable IaC patterns and guardrails.
Own CI/CD pipelines, deployment strategies, and environment management; diagnose and resolve build, runtime, and networking issues across staging/production.
Partner with client Cloud/Platform teams to align on architecture, security, IAM policies, networking (VPCs, subnets, peering), monitoring, and cost controls.
Translate ambiguous client requirements into clear technical designs, RFCs, and deliverable roadmaps; set expectations and communicate trade-offs.
Establish observability and reliability practices (logs, metrics, traces, alerts, runbooks, SLOs); lead incident response and postmortems.
Contribute to data and model integration patterns for LLMs/ML (prompting, retrieval, evaluation, safety/guardrails, latency/cost optimization).
Uphold code quality via reviews, testing, and automated validation; mentor engineers and raise the technical bar.

Předpoklady a dovednosti

Core requirements:

6+ years of professional software engineering experience, including senior-level ownership of production systems.
Strong proficiency in:
- TypeScript: building backend services (Node.js), APIs, event-driven/serverless patterns, testing.
- Python: data pipelines, backend services, SDKs/CLI tools, integration with AI/ML libraries.
- AWS: deep hands-on with IAM, VPC, Lambda, ECS/EKS, API Gateway/ALB, S3, CloudWatch, CloudFormation/CDK, Secrets Manager/SSM, Step Functions or event buses.
Infrastructure as Code: fluent with AWS CDK or similar (CDKTF, Pulumi, SST); ability to design modular stacks and handle multi-account, multi-region setups.
CI/CD and DevOps: experience with GitHub Actions/GitLab CI/CodeBuild, artifact management, testing strategies, blue/green or canary deployments.
Production troubleshooting: strong diagnostic skills across logs/metrics/traces, container/serverless runtimes, networking/DNS, and permissions.
Client-facing communication: proven ability to gather requirements, write design docs, present trade-offs, and collaborate with enterprise cloud/platform teams.
Security and compliance mindset: least-privilege IAM, secrets management, data privacy, auditability, cost/performance monitoring.

Nice to have:

AI/ML ecosystem: experience with LLM frameworks (LangChain, LlamaIndex), vector databases (OpenSearch, Pinecone, pgvector), embeddings, RAG, prompt evaluation.
AWS AI services: Bedrock, SageMaker, Comprehend, or integrating third-party model providers (OpenAI, Anthropic, Azure OpenAI).
Data engineering: ETL/ELT, event streaming (Kafka/Kinesis), batch/stream processing, Lake/Lakehouse patterns.
Containers and orchestration: Docker, ECS/Fargate, EKS, Helm; serverless-first architectures.
Observability stack: CloudWatch, OpenTelemetry, Datadog/New Relic, centralized logging.
Compliance/domain exposure: SOC2, HIPAA, PCI, or enterprise security reviews.

How you’ll work:

Lead by example with hands-on coding and architecture.
Operate with high ownership across design, delivery, and operations.
Collaborate closely with client stakeholders; communicate clearly and proactively.
Balance speed and rigor with high-quality testing, monitoring, and documentation.