Intelligent/Agentic 6 Automation Developer (BB69FT RM 3977)

Position: Intelligent/Agentic 6 Automation Developer (BB69FT RM 3977)

Agentic AI & MLOps Engineering

• Design, build, and deploy agentic AI systems using LLMs, tool orchestration, and multi-agent workflows. Experience building multi-agent systems or autonomous workflows.
• Develop and optimize RAG pipelines using vector databases and retrieval strategies.
• Build robust prompt frameworks, evaluation pipelines, and guardrails for safe and reliable AI behaviour.
• Integrate LLM-based systems with enterprise APIs, data platforms, and operational systems.
• Implement observability, feedback loops, and performance monitoring for agentic systems in production.
• Design and implement CI/CD pipelines for ML and GenAI systems.
• Build infrastructure for model training, fine-tuning, evaluation, and deployment.
• Develop reusable internal AI SDKs, templates, and tooling to accelerate development across teams.
• Automate infrastructure provisioning using Infrastructure as Code (IaC).
• Ensure high availability, scalability, cost optimization, and security of AI workloads.
• Deploy and manage cloud-native AI workloads across AWS, Azure, or GCP.
• Implement monitoring, logging, and alerting frameworks for AI systems.
• Optimize GPU/accelerated workloads for performance and cost efficiency.
• Expertise in Prometheus, Loki, Grafana, Kibana, Open Telemetry and other observability tools will be a plus.
• Partner with Data Science and Engineering teams to productionize ML and GenAI solutions.
• Work closely with business teams to deploy AI use cases tied to KPIs such as predictive maintenance, process optimization, and engineering productivity.

Qualifications

• 8 12+ years of professional experience in software engineering with Agentic AI, ML platform engineering.
• BS/MS in Computer Science, Electrical Engineering, Data Science, or related field.
• 3+ years of hands-on experience with Generative AI and LLM-based systems in production environments.
• Proven experience deploying ML/LLM systems with cloud-native infrastructure.

Technical Expertise

• Strong programming skills in Python.
• Experience with LLM frameworks (LangChain, LlamaIndex, Semantic Kernel, or similar).Deep understanding of RAG architectures and vector databases (PG vector, Milvus, FAISS, Pinecone, Weaviate, etc.).
• CI/CD tools (GitHub Actions, GitLab CI, Jenkins, ArgoCD).
• Cloud platforms (AWS, Azure, or GCP). Experience with MLOps tools (MLflow, Kubeflow, SageMaker, Vertex AI, etc.).Observability tools (Prometheus, Grafana, Open-Telemetry, etc.).

Preferred

• Exposure to manufacturing, semiconductor, or high-tech enterprise environments.
• Experience optimizing inference workloads (GPU, model quantization, batching strategies).
• Familiarity with security, compliance, and governance frameworks for enterprise AI.
• Contributions to internal AI platforms or developer productivity tooling

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