Position: Senior Engineer - Gen AI Job Description: Job Profile Specification: Senior Generative AI / Agentic AI Engineer (5–6 years)s Role summary: • Senior-level engineer (5–6 years of professional experience) focused on designing, building, and deploying production-grade generative AI and agentic-AI solutions. • Responsible for delivering secure, scalable, and business-oriented AI systems that operate on structured and unstructured data and enable AI-driven decision-making Required experience • 5–6 years of industry experience in software engineering and AI-related roles. • Minimum 2-3 years of direct experience with Generative AI and Large Language Models (LLMs). Key Responsibilities: • Architect, develop, test, and deploy generative-AI solutions (online/offline LLMs, SLMs, TLMs) for domain-specific use cases. • Design and implement agentic AI workflows and orchestration using frameworks such as LangGraph, Crew AI, or equivalent. • Integrate enterprise knowledge bases and external data sources via vector databases and Retrieval-Augmented Generation (RAG). • Build and productionize ingestion, preprocessing, indexing, and retrieval pipelines for structured and unstructured data (text, tables, documents, images). • Implement fine-tuning, prompt engineering, evaluation metrics, A/B testing, and iterative model improvement cycles. • Conduct/model red-teaming and vulnerability assessments of LLMs and chat systems using tools like Garak (Generative AI Red-teaming & Assessment Kit). • Collaborate with MLOps/platform teams to containerize, monitor, version, and scale models (CI/CD, model registry, observability). • Ensure model safety, bias mitigation, access controls, and data privacy compliance in deployed solutions. • Translate business requirements into technical designs with clear performance, cost, and safety constraints. Required Skills and Experience: • Strong proficiency in Python and experience with ML/AI libraries (scikit-learn, TensorFlow, PyTorch, Hugging Face ecosystem). • Hands-on experience with LLMs, RAG, vector databases, and retrieval pipelines. • Practical experience deploying agentic workflows and building multi-step, tool-enabled agents. • Experience using Garak (or similar LLM red-teaming/vulnerability scanners) to identify model weaknesses and harden deployments. • Demonstrated experience implementing content filtering / moderation systems. • Solid skills working with structured and unstructured data and advanced feature engineering. • Familiarity with cloud GenAI platforms and services (Azure AI Services preferred; AWS/GCP acceptable). • Experience building APIs/microservices; containerization (Docker), orchestration (Kubernetes). • Strong understanding of model evaluation, performance profiling, inference cost optimization, and observability. • Good knowledge of security, data governance, and privacy best practices for AI systems. Preferred / differentiating qualifications • Hands-on fine-tuning experience and parameter-efficient tuning methods. • Experience with multimodal models and retrieval-augmented multimodal pipelines. • Prior work on agentic safety, tool-use constraints, LLM application firewalls, or human-in-the-loop systems. • Familiarity with LangChain, LangGraph, Crew AI, or similar orchestration libraries. Values & behaviours • AI-first thinking: consistently seeks AI-enabled solutions to business problems. • Data-driven mindset: makes decisions based on measurable insights and metrics. • Collaboration & agility: effective contributor in cross-functional, fast-paced teams. • Problem-solving orientation: looks beyond the obvious to unlock product and business value. • Business impact focus: designs solutions with measurable outcomes and real adoption. • Continuous learning: stays current with academic research, open-source tooling, and best practices. Location: IN-GJ-Ahmedabad, India-Ognaj (eInfochips) Time Type: Full time Job Category: Engineering Services