Responsibilities
Design and build AI‑augmented migration tooling that automates discovery, code transformation, containerisation, and validation across compute platforms. Engineer agentic workflows to analyse legacy workloads, generate migration artefacts (Dockerfiles, Helm/Kubernetes manifests, CI/CD pipeline definitions), and produce reviewable pull requests against real codebases.
Build guardrails that provide automated validation, rollback, and continuous verification so AI‑generated migration changes are safe to ship at scale. Establish reusable patterns, prompts, evals, and reference implementations enabling the migration organisation to apply these tools consistently and reliably.
Partner closely with platform engineering teams that build and operate GKP, GCS, Gaia VSI, and the container golden path to ensure tooling targets the correct end state. Work directly with migration execution and enablement teams to understand real blockers and encode solutions into tooling rather than one‑off fixes.
Measure and improve the quality, cost, and throughput of AI‑driven migration, treating model‑output quality and human‑review load as engineering metrics to optimise. Contribute to the firm’s practice for safe, effective use of agentic coding tools on production codebases.
Qualifications
- Strong software engineering fundamentals and hands‑on delivery in Python, Go, or Java.
- Production‑grade experience with AI coding assistants (Claude Code, GitHub Copilot, or equivalent) to build and ship real software.
- Experience building automation and tooling that operates on real codebases: code parsing/transformation, templating, and generating reviewable pull requests.
- Knowledge of cloud‑native platforms and primitives: Kubernetes, Docker/OCI containers, and at least one of AWS, GCP, or Cloud Foundry/VCF.
- CI/CD and automated deployment pipeline experience.
- Designing validation guardrails for automated change, testing, verification, and safe rollback.
- End‑to‑end application infrastructure concerns such as authentication/authorization and systems integration.
- Consultative, problem‑solving mindset with clear communication of technical concepts.
- Excellent written and spoken communication skills.
- Bachelor’s degree in Computer Science, Computer Engineering, or a related field plus working experience as a Software Engineer, Application Developer, or related role.
- Attributes: builder’s bias (ship tools others depend on), success measured by migrations completed, comfort at the AI frontier, healthy scepticism, optimism, adaptability, respect for others, and continuous skill improvement.
Preferred Qualifications
- Experience building on top of LLM APIs: agent frameworks, tool/function calling, retrieval, and writing evals to measure output quality.
- Prompt and context engineering, including cost/latency/quality trade‑offs.
- Container build and supply‑chain tooling: Dockerfiles, buildpacks/Kaniko, SBOM, image signing, hardened base images.
- Infrastructure‑as‑code tools such as HashiCorp Terraform.
- Static analysis, AST‑level code transformation, or compiler/language‑tooling experience.
- Large‑scale migration or modernisation programmes and proficiency managing large infrastructure deployments (compute, container systems, storage, networking).
- Knowledge of global financial services regulatory and compliance considerations related to workload deployment.
- Experience with databases and messaging technologies such as MySQL, Cassandra, Kafka, CockroachDB, or Oracle.
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