Senior Generative AI Engineer

Hi,I hope you are doing well,Role: Senior Generative AI Engineer (LLM & Agent Systems)Location: Bangalore, Remote - (Occasionally 2 times in a month)Experience: 3+Duration: Long termNeed local to Bangalore profilesJob description: AI/ML System Implementation & Integration: Translate requirements into well-engineered components (pipelines, vector stores, prompt/agent logic, evaluation hooks) and implement them in partnership with the platform/architecture team.Application & Agent Development:Build and maintain LLM-based agents/services that securely call enterprise tools (ServiceNow, Salesforce, Oracle, etc.) using approved APIs and tool-calling frameworks.Create lightweight internal SDKs/utilities where needed.RAG & Search Enablement: Configure and optimize RAG workflows (chunking, embeddings, metadata filters) and integrate with existing search/vector infrastructure—escalating architecture changes to designated architects.MLOps & SDLC Practices: Follow and improve team standards for CI/CD, testing, prompt/model versioning, and observability.Own feature delivery through dev/test/prod, coordinating with release managers.Governance, Security & Compliance: Apply established guardrails (PII redaction, policy checks, access controls).Partner with InfoSec and architects to close gaps; document decisions and risks.Metrics & Reporting: Instrument services with KPIs (latency, cost, accuracy/quality) and build lightweight dashboards. Deep BI/reporting not primary. Documentation & Communication:Write clear technical docs (APIs, workflows, runbooks), user stories, and acceptance criteria. Support and sometimes lead UAT/test activities. Collaboration & Mentorship:Facilitate working sessions with stakeholders; mentor junior engineers through code reviews and pair programming; provide concise updates and risk flags. Education & Experience:Bachelor's degree and eight years of relevant experience or a combination of education and relevant experience.Required Knowledge, Skills, and Abilities: Agent/Agentic Framework Experience: Built and shipped at least one production LLM agent or agentic workflow using frameworks such as LangGraph, LangChain, CrewAI/AutoGen, Google Agent Builder/Vertex AI Agents (or equivalent).Able to explain tool selection, orchestration logic, and post‑deployment support.Proven Delivery: Implemented 3+ AI/ML projects and 2+ GenAI/LLM projects in production, with operational support (monitoring, tuning, incident response).Projects should serve sizable user populations and demonstrate measurable efficiency gains.Strong understanding of AI/ML concepts (LLMs/transformers and classical ML) and experience designing, developing, testing, and deploying AI-driven applications.Programming Expertise: Python (primary) plus experience with Node.js/Next.js/React/TypeScript and Java; demonstrated ability to quickly learn new tools/frameworks.Experience with cloud AI stacks (e.g., Google Vertex AI, AWS Bedrock, Azure OpenAI) and vector/search technologies (Pinecone, Elastic/OpenSearch, FAISS, Milvus, etc.).Knowledge of data design/architecture, relational and NoSQL databases, and data modeling.Thorough understanding of SDLC, MLOps, and quality control practices.Ability to define/solve logical problems for highly technical applications; strong problem-solving and systematic troubleshooting skills.Excellent communication, listening, negotiation, and conflict resolution skills; ability to bridge functional and technical resources.Desired Knowledge, Skills, and Abilities: MLOps Tooling: MLflow, Kubeflow, Vertex Pipelines, SageMaker Pipelines; LangSmith/PromptLayer/Weights & Biases.Open Source Savvy: Experience working with, customizing, and improving open-source solutions; comfortable contributing fixes/features upstream.Rapid Tech Adoption: Demonstrated ability to pick up a new technology/framework quickly and deliver production value with it.GenAI Frameworks: LangChain, LlamaIndex, DSPy, Haystack, LangGraph, Agent Engine, Google ADK, AWS AgentCore, CrewAI/AutoGen.Security & Governance: Implementing AI guardrails, red-teaming, and policy enforcement frameworks.Enterprise Integrations: ServiceNow, Salesforce, Oracle Financials, or others.UI Development: React/Next.js/Tailwind for internal tools.Prompt engineering at scale: Structured prompts (JSON/function-calling), templates, version control; automated/offline & online evals (rubrics, hallucination/bias checks, A/B tests, golden sets).Parameter‑efficient fine‑tuning (LoRA/QLoRA/adapters), supervised instruction tuning; hosting open‑weight models (Llama/Mistral/Qwen) with vLLM/TGI/Ollama. Safety/guardrails frameworks (Guardrails.ai, NeMo Guardrails, Azure/AWS safety filters) and jailbreak/drift detection.Hybrid search & reranking (BM25+dense, Cohere/Voyage/Jina rerankers), synthetic data generation, provenance/watermarking.Telemetry & governance: prompt/model drift monitoring, policy‑as‑code, audit logging, red‑teaming playbooks.Certifications and Licenses: Google/AWS/Azure ML/AI certifications or strong demonstrable portfolio of production AI systems.Sameer Dudekula|Lead US IT Technical recruiterMinisoft Technologies LLC+91-7780246304 | sameerd@minisofttech.comhttps://www.linkedin.com/in/sameer-sam-a1b240b9/