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Designation AI Integration Engineer

Job Description

- Build end‑to‑end AI/ML pipelines (training → evaluation → deployment) using MLflow/Kubeflow/Databricks/Weights & Biases with experiment tracking and model registries.
- Develop models with Python using PyTorch, Tensor Flow, JAX, scikit‑learn, and Hugging Face Transformers, package as reproducible services.
- Implement LLM/RAG systems with Lang Chain, Llama Index, Semantic Kernel and vector DBs (Pinecone, Weaviate, Milvus, FAISS, Chroma) for semantic retrieval and grounding.
- Fine‑tune and optimize models using PEFT/LoRA/QLoRA, Deep Speed/Accelerate, distillation, and quantization; export/optimize via ONNX Runtime/Torch Script/TensorRT.
- Engineer scalable model serving with KServe, Seldon Core, BentoML, Ray Serve, NVIDIA Triton, supporting A/B, canary, shadow deployments.
- Build evaluation harnesses (offline/online) with Ragas, Tru Lens, Promptfoo, golden datasets, and regression gates integrated into CI/CD.
- Construct feature stores (, Feast) and data contracts (Protobuf/Avro/Pydantic); enforce data quality with Great Expectations/Deequ.
- Orchestrate event‑driven pipelines with Airflow/Prefect/Dagster; streaming/messaging via Kafka/RabbitMQ/NATS and schema registries.
- Design Python microservices using FastAPI/gRPC; integrate with downstream systems via REST/GraphQL; write robust automation in Python/Bash/Power Shell and SQL for data ops.
- Use notebooks (Jupyter) and packaging (Poetry/pip/conda) with virtualenvs, environment locking, and artifacts suitable for promotion across stages.
- Apply testing & quality: pytest, unit/integration/e2e tests, property‑based (hypothesis), linters/formatters (ruff/flake8, black), type checks (mypy/pyright), pre‑commit.
- Deliver IaC with Terraform/Pulumi; manage config via Helm/Kustomize; implement Git Ops with Argo CD/Flux on managed/self‑hosted Kubernetes.
- Build secure CI/CD (Git Hub Actions/Git Lab CI/Jenkins/Azure Dev Ops)



for app/data/ML artifacts, artifact promotion, provenance, and automated rollbacks.
- Embed Dev SecOps: SAST/DAST/IAST (Snyk/Checkmarx/Sonar Qube), container & IaC scanning (Trivy), dependency hygiene (Dependabot/Renovate), SBOM (Syft/CycloneDX).
- Enforce policy‑as‑code (OPA/Gatekeeper, Kyverno), image signing/verification (Sigstore/cosign), supply‑chain standards (SLSA, in‑toto).
- Manage secrets/KMS with Vault and native managers; adopt short‑lived workload identities, mTLS, and least‑privilege RBAC/ABAC in clusters and pipelines.
- Implement AI safety & governance: prompt‑injection defenses, output filtering, PII redaction, guardrails ( Guardrails/Presidio), policy checks.
- Monitor model/data drift, bias, and performance with Evidently/Why Labs/Arize/Fiddler; unify telemetry via Open Telemetry, Prometheus, Grafana, ELK/Loki, Jaeger.
- Optimize compute/GPU: CUDA/cuDNN/NCCL, HPA/VPA/KEDA, effective batching, caching, concurrency control; track cost and latency SLOs.
- Implement progressive delivery for services/models (blue/green, canary, shadow) using Argo Rollouts/Flagger with instant rollback and health checks.
- Operate API gateways and service mesh (Kong/NGINX/Envoy, Istio/Linkerd) for rate limiting, mTLS, authN/Z, and zero‑trust patterns.
- Ensure privacy/compliance (GDPR/CCPA/DPDP/ISO 27001): data minimization, masking/tokenization, DLP, lineage (Open Lineage/Marquez), model cards/data sheets.
- Collaborate with security, data, and platform teams to publish golden paths, templates, and reference implementations for repeatable AI delivery.
- Contribute to code/design reviews and SRE practices (SLIs/SLOs/error budgets), on‑call readiness, incident response, and blameless post‑mortems.

Desired Profile

- Looking for a Dev SecOps & AI Engineer with 4–7 years of hands‑on experience in cloud platforms, automation, and AI/ML engineering workflows.
- Strong expertise in Terraform, Kubernetes,



Helm, Docker, and modern CI/CD pipelines using Git Hub Actions, Git Lab CI, Jenkins, or Azure Dev Ops.
- Proficient in Python with experience in FastAPI, ML libraries (PyTorch/Tensor Flow), and scripting using Bash or Power Shell for automation.
- Solid experience in Dev SecOps practices including SAST/DAST, container/IaC scanning, secrets scanning, SBOM, and policy-as-code frameworks.
- Hands‑on exposure to MLOps and AI integration using tools like MLflow, Kubeflow, Weights & Biases, KServe, Seldon Core, or BentoML.
- Experience building or integrating RAG/LLM pipelines using Lang Chain, Llama Index, or vector databases (Pinecone/FAISS/Weaviate).
- Strong cloud fundamentals across AWS/Azure/GCP with ability to architect secure, automated infrastructure via IaC and Git Ops (Argo CD/Flux).
- Familiarity with monitoring and observability stacks (Prometheus, Grafana, Open Telemetry, ELK/Loki) for application and model performance.
- Strong troubleshooting, problem‑solving, and system debugging skills with a collaborative, engineering‑first mindset.
- Excellent communication skills with ability to work cross‑functionally with Data, AI/ML, Dev Ops, Security, and Platform Engineering teams.

Experience 4 to 7 years

Education / BS in Computer Science

Technical Skills & Certifications

- Terraform, Pulumi, and IaC for automated cloud and platform provisioning.
- Kubernetes, Docker/Podman, Helm, and Kustomize for container orchestration and packaging.
- CI/CD pipelines using Git Hub Actions, Git Lab CI, Jenkins, and Azure Dev Ops.
- Proficient in Python (FastAPI, ML/LLM libraries) and scripting with Bash/Power Shell.
- Dev SecOps tooling: Snyk, Sonar Qube, Trivy, Checkmarx, Git Leaks, and secret scanning.
- MLOps platforms: MLflow, Kubeflow, W&B;, Azure ML, Vertex AI for model lifecycle management.
- Model serving frameworks: KServe, Seldon Core, BentoML, Ray Serve for scalable inference.
- RAG/LLM integration: Lang Chain, Llama Index, vector DBs (Pinecone, Weaviate, FAISS, Chroma).
- Monitoring & observability: Prometheus, Grafana, ELK/Loki, Open Telemetry, Jaeger.
- Git Ops tools (Argo CD, Flux), configuration management (Ansible/Puppet), and serverless functions.

EY | Building a better working world

📌 Tech S And T - AI Integration Engineer Senior - G (India)
🏢 EY
📍 India