| Job Description: |
Location: Bangalore
Role Descriptions: GenAI Engineer - L2
Experience Required: 6-8
Desirable Skills:
Must-Have**
(Ideally should not be more than 3-5)
1) 6 plus years professional software engineering, including 3+ year building and shipping GenAI or LLM-driven products.
2) Architect, develop, and deploy GenAI services that ingest SCADA, PI System, WITSML, and reservoir data to deliver insights for drilling optimization, equipment reliability, and emissions reduction.
3) Fine-tune and evaluate large language and vision models on domain-specific corpora (well files, P&IDs, procedures, regulatory filings).
4) Build secure, scalable APIs and micro-services in Python/TypeScript; containerize with Docker and serve on Kubernetes/EKS or OpenShift.
5) Implement retrieval-augmented generation pipelines with vector databases (e.g., OpenSearch, Milvus) to enable fast technical-document Q&A for engineers and field operators.
6) Optimize model inference on GPUs/accelerators using DeepSpeed, TensorRT, or vLLM; benchmark latency, throughput, and cost.
7) Embed GenAI capabilities into web, mobile, and edge applications used at well sites, plants, and control centres, ensuring robust observability and rollback.
8) Uphold best-practice software engineering: CI/CD (GitHub Actions, ArgoCD), automated testing, IaC (Terraform/Pulumi), and secure coding aligned with AER regulatory requirements.
9) Monitor academic and industry advances (RLHF, RAG, agentic workflows) and champion pragmatic adoption in oil & gas contexts.
10) Good communication, analytical, presentation and documentation skills.
Good-to-Have
1) Experience integrating GenAI with historian data, geoscience interpretation tools (Petrel, Kingdom), or maintenance systems (SAP PM, Maximo).
2) Contributions to open-source GenAI/ML projects or published papers.
3) Familiarity with LangChain, LlamaIndex, or similar orchestration frameworks.
4) Knowledge of energy-sector regulations (AER, CAPP) impacting data use and model governance.
5) Background in real-time analytics for production optimization or flare/emissions monitoring.
Technical Skills
1) Advanced Python (FastAPI, PyTorch, Hugging Face); plus proficiency in TypeScript/Node.js, Go, or Java.
2) Production experience on AWS or Azure with GPU workloads (SageMaker, Bedrock, Azure ML).
3) Working knowledge of oil & gas data formats and systems (e.g., LAS, WITSML, PI AF, OSDU) or proven ability to learn quickly.
4) Strong grasp of algorithms, distributed systems, and data engineering (Spark, Kafka, Delta Lake).
Commitment to responsible AI, data governance, and cybersecurity best practices for critical infrastructure
Soft Skills 1) Problem-Solving:
a. Analytical thinking and the ability to troubleshoot complex issues.
b. Creativity in designing innovative solutions.
2) Communication:
a. Effective communication with technical and non-technical stakeholders.
b. Ability to document and present architectural designs and solutions clearly.
3) Continuous Learning:
a. Staying updated with the latest Azure features, best practices, and industry trends.
b. Pursuing relevant certifications and training programs. |
| Comments for Suppliers: |
Candidate must be available for virtual drive on 6th Feb |
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