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GenAI Engineer

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Onsite

GenAI Engineer

Hiringhood

GenAI Engineer

Skills

PythonData ScienceMicroservicesKafkaSnowflakeDatabricksData AnalysisMachine LearningAI

1 month ago

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Important information


Contract type:

Permanent

Location:

Bengaluru, Karnataka, India

Work mode:

Onsite

Published on:

27 September 2026

What they need


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

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