Gen AI Engineer
Arrow Ec2–3 yrsIndoreOn-siteDirect career pageEst. 10–20 LPA
Posted 1d ago
Reach people at Arrow Ec
People at this company you can reach
Log in to see who works here
Create a free account or log in to see the people at Arrow Ec you could write to:
- Recruiters & HR
- People in this function
- Work addresses
Your match
Against your primary resume
Log in to see your match score
Create a free account or log in to unlock your CV match score across:
- Role fit
- Experience
- Industry relevance
Protocol Intelligence
How competitive this role is
Competition
Background fit
Strictness
Log in to see why each signal reads the way it does.
Job description
Structured overview of role & requirements
About This Role
- Design, develop, test, and deploy production-grade generative and agentic AI solutions including LLMs for domain-specific applications.
- Build ingestion, preprocessing, indexing, and retrieval pipelines for structured/unstructured data integrating enterprise knowledge bases using vector databases and Retrieval-Augmented Generation.
- Ensure model safety, bias mitigation, access control, privacy compliance, and collaborate with MLOps teams to containerize, monitor, and scale AI models with a focus on performance, cost, and security constraints.
Minimum Requirements
- 2-3 years of direct experience with Generative AI and Large Language Models (LLMs).
- Strong proficiency in Python and ML/AI libraries such as TensorFlow, PyTorch, and Hugging Face ecosystem.
- Hands-on experience with agentic AI workflows, LangGraph/Crew AI or equivalent orchestration frameworks, vector databases, RAG pipelines, and red-teaming tools like Garak.
- Work Experience Required: 2-3 years in relevant AI engineering roles; Location: Indore, Madhya Pradesh, India.
Ideal Candidate Profile
- Experienced AI engineer able to translate business requirements into secure, scalable generative AI systems with measurable performance and cost metrics.
- Proficient in deploying multi-step agentic workflows with advanced evaluation, tuning, and vulnerability assessment techniques.
- Skilled in integrating cloud GenAI platforms (preferably Azure AI Services), containerization (Docker), Kubernetes orchestration, and operating in fast-paced, cross-functional environments.