Description: Skills: Digital : AI Platform Engineer

Required Technical Skill Set : AI Platform Engineering, Prompt Engineering &

- Model Evaluation Frameworks, Infrastructure as Code (Terraform), Python, Security as Code / Policy as Code, Cloud Platforms (GCP / Azure / AWS), CI/CD &
- MLOps Pipelines, API Gateways &
- Service Mesh, AI Guardrails &
- Governance Integration

Experience Range: 7 – 12 Years overall

Technical experience (with 2–3+ years hands-on experience in AI/ML platforms, GenAI enablement, or MLOps)

Role Descriptions

Must-Have (Candidates must demonstrate depth in core infrastructure/platform engineering and a blend of the following specialisms)

- AI Platform Engineering &
- Foundation: Proven track record in designing, building, and operating enterprise-scale AI platforms, GenAI gateways, model routing endpoints, and developer sandboxes hosted on cloud environments (GCP Vertex AI, Azure AI Studio / OpenAI Service, or AWS Bedrock).
- Prompt Engineering &
- Systematic Evaluation: Solid hands-on experience with prompt design, metaprompt optimization, few-shot prompting, and automated model evaluation frameworks (evaluating grounding, relevance, toxicity, hallucination, and RAG faithfulness using frameworks such as Ragas, DeepEval, PromptFoo, Pegasus, or custom LLM-as-a-judge harnesses).
- Infrastructure as Code (IaC): Advanced expertise in Terraform for orchestrating complex cloud landing zones, container platforms (GKE / AKS / EKS), AI developer workspaces, model registries, and secure networking topologies.
- Security as Code &
- Policy as Code:



Practical experience embedding automated security, compliance, and governance policies into delivery pipelines using Open Policy Agent (OPA), Rego, Checkov, tfsec, Terrascan, or Cloud Security Posture Management (CSPM) baselines.
- Software Development &
- Automation: High proficiency in Python (async programming, SDK development, RESTful / gRPC APIs, FastAPI) and building scalable automation tooling for developer workflows.
- Secure CI/CD &
- MLOps Tooling: Experience designing automated release pipelines (GitHub Actions, GitLab CI, Azure DevOps) for model deployment, configuration versioning, prompt promotion, and artifact validation.

Good-to-Have

- Experience integrating enterprise AI guardrails and filtering mechanisms (e.g., NeMo Guardrails, Llama Guard, Azure AI Content Safety).
- Familiarity with containerisation, Kubernetes, Istio service mesh, API gateway management, and rate limiting / token metering solutions.
- Knowledge of AI Governance, Risk &
- Compliance standards (NIST AI RMF, ISO/IEC 42001, OWASP Top 10 for LLM/GenAI).
- Cloud and security certifications: HashiCorp Certified Terraform Associate, GCP/Azure Cloud DevOps Engineer, Cloud Security Specialist, or equivalent.

Custom Fields

Name: Work Location CDF

Value: ~TRIL - Infopark - SEZ~

Name: Assets

Value: None

Name: Requisition ID

Value: 11001494

Name: Parent

Value: IS-BFSI-UK1-Parent

Name: Business Vertical

Value: CL-BFSI-UK-EMEA-APAC

Name: Type of Asset

Value: None

Name: Work Assignment Location

Value: Onsite

Name: Child

Value: IS-BFSI-UK1-1.1

📌 IND_Senior Security Engineer (Mumbai)
🏢 Artech Infosystems
📍 Mumbai