Software Engineer

Travel: approximately 25% when necessary. Office attendance: the exact weekly onsite schedule remains pending. Compensation guidance: USD 150,000–220,000 annual base, with potential flexibility. AI Led Engineering – Enterprise AI, Cloud and Platform Transformation Role overview: A senior technical leader combining enterprise AI engineering, cloud/platform architecture, DevOps/SRE and observability to modernize mission-critical systems and operational processes.

Key Responsibilities: Lead architecture and engineering for enterprise AI, cloud and platform transformation initiatives. Design production-ready AI/ML and GenAI capabilities and integrate them with enterprise platforms. Improve reliability, automation, deployment, monitoring and operational performance of mission-critical systems. Guide platform engineering, CI/CD, container orchestration, infrastructure automation and observability practices. Address security, governance, scalability and operational requirements in enterprise or regulated environments.

Required: Experience and Technical Skills: Target profile: 12+ years across AI, DevOps, cloud, SRE or platform disciplines. Target profile: 3+ years hands-on AI stack experience and 5+ years enterprise platform design experience. Target profile: 3+ years AIOps/observability experience. Python is mandatory. Experience with enterprise cloud architecture and production AI/ML or GenAI systems. Knowledge of cloud platforms such as AWS, Azure or GCP; CI/CD; Kubernetes; Docker; Terraform; and platform automation. Preferred / Additional Experience: GenAI/LLM/RAG, vector databases, model lifecycle, AWS Bedrock or SageMaker, and MCP/agent integrations. Tools such as Kiro, GitHub Copilot, Datadog, Dynatrace, Splunk, Prometheus or Open Telemetry. Service mesh, SRE practices, AIOps and observability in complex enterprise environments. What Candidates Should Be Able to Demonstrate A specific enterprise platform or AI transformation personally led or implemented. Evidence of hands-on Python and AI stack work, plus enterprise platform design. Examples of AIOps/observability, reliability improvements, automation, deployment outcomes or measurable operational impact.