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    Job · 19536267

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    GenAI Engineer

    Hiringhood · Bengaluru · onsite · Posted 23d ago

    Not disclosed4–8 yrsfulltimeSourced fromFoundit

    About a minute. You'll make an account on the way through.

    About this role

    GenAI Engineer

    Location: Bengaluru Manyata Tech Park

    Work Mode: Hybrid – 3 Days Work from Office

    Experience: 4–8 Years

    Employment Type: Full Time

    Notice Period: Immediate to 15 Days

    Open Positions: 1

    About the Company

    We are a growing technology company building innovative AI, GenAI, and intelligent industrial technology solutions. The organization focuses on developing scalable AI-powered products that combine Generative AI, Agentic AI, machine learning, IoT, time-series data, and modern cloud technologies to solve complex real-world business and operational challenges.

    About the Role

    We are looking for a GenAI Engineer with 4–8 years of experience across Data Science, Machine Learning, AI Engineering, or GenAI development. The ideal candidate will have hands-on experience building and deploying GenAI and AgenticAI applications in production, with strong expertise in Python, LLMs, RAG, AI agents, orchestration frameworks, and scalable backend systems.

    Key Skills

    • 4–8 years of experience in Data Science, Machine Learning, AI Engineering, or GenAI
    • Hands-on experience building and deploying GenAI / AgenticAI applications
    • Strong experience with LangChain, CrewAI, AutoGen, LangGraph, or similar frameworks
    • Strong understanding of:
    • Prompt engineering
    • Embeddings
    • RAG
    • Tool calling
    • LLM orchestration
    • AI agents
    • LLM evaluation
    • Experience with time-series modeling
    • Knowledge of HITL, LLM-as-a-Judge, deterministic evaluation, and fine-tuning workflows
    • Experience with LangSmith or equivalent observability/experimentation tools
    • Strong proficiency in Python
    • Experience building REST and/or gRPC APIs and microservices
    • Understanding of CI/CD, distributed systems, and production system design
    • Experience optimizing AI inference performance, latency, and API costs
    • Understanding of cloud-native development and scalable AI infrastructure

    Good to Have

    • Experience in industrial systems, IoT, digital twins, or manufacturing technologies
    • Time-series modeling, anomaly detection, predictive maintenance, or sensor analytics
    • Kafka, NSQ, or similar event-driven technologies
    • Databricks, BigQuery, Snowflake, or lakehouse architectures
    • Knowledge graphs or context graphs
    • Experience working with multimodal AI involving structured, unstructured, and sensor-driven data

    Roles & Responsibilities

    • Own the end-to-end development of GenAI and AgenticAI solutions, from prototyping to production deployment and monitoring
    • Build intelligent systems combining time-series modeling, signal processing, LLMs, embeddings, agents, and retrieval pipelines
    • Design and implement scalable RAG pipelines, tool-calling workflows, multi-agent systems, and evaluation frameworks
    • Develop AI applications integrating sensor-based time-series data, unstructured text, and machine learning outputs
    • Drive technical decisions around architecture, tooling, experimentation, and deployment
    • Collaborate with Product, Engineering, Applied AI, and domain teams to translate customer problems into scalable solutions
    • Contribute to data pipelines, deployment infrastructure, evaluation frameworks, MLOps, and LLMOps
    • Build backend services using Python, including REST/gRPC APIs and workflow orchestration services
    • Monitor AI systems for performance, drift, reliability, latency, and cost efficiency
    • Continuously improve model quality and production scalability
    • Collaborate with customers and internal stakeholders to prototype and deliver AI-driven solutions

    Education

    Bachelor's degree in Computer Science, Information Technology, Engineering, or a related technical field (B.Tech / B.E. or equivalent).

    Interview Process

    L1: Technical Discussion L2: Coding & Technical Discussion – 1.5 Hours

    Note: L2 is Face-to-Face and candidates are required to bring their own laptop for the coding round.

    HR: HR Discussion

    Additional Details

    • Hybrid: 3 days from office
    • Location: Manyata Tech Park, Bengaluru

    Sourced from foundit

    Skills

    Scalable AI infrastructureRetrieval Augmented GenerationLangSmithAutoGenPrompt EngineeringLLM orchestrationCrewaiDistributed SystemsHITLEmbeddingstime-series modelingCloud-Native DevelopmentLLM EvaluationgRPC APIstool callingPythonMicroservicesLanggraphLangchainAgentic Ai

    GenAI Engineer · waiting for your command