Key Responsibilities

- Design and develop

Agentic AI systems with multi-step reasoning, tool use, and workflow orchestration.

- Integrate AI agents into client applications and business workflows

.

- Build, fine-tune, and evaluate

ML/LLM models using established training platforms and pipelines.

- Collaborate with clients and engineering teams to gather requirements and translate business problems into AI solutions

.

- Integrate agentic workflows using

APIs, SDKs, and platform-specific tools across web, mobile, and enterprise applications.

- Develop

RAG pipelines, vector databases, embeddings, and prompt/context engineering strategies.

- Define evaluation metrics and conduct model/agent performance experiments

.

- Optimize AI solutions for scalability, latency, cost, security, observability, and reliability

.

- Work with data engineering, product, and QA teams to deliver production-ready AI features.

- Document architecture, model behavior, integration patterns, and deployment processes

.

- Stay updated on the

Agentic AI and ML ecosystem and recommend relevant frameworks and platforms.

Required Skills & Experience

- 3–5 years of software engineering experience

, including hands-on AI/ML application development.





- Experience building

Agentic AI systems using LangChain, LangGraph, AutoGen, CrewAI, or similar frameworks.

- Experience integrating

AI/ML solutions into web, mobile, or enterprise applications using APIs and SDKs.

- Knowledge of ML platforms such as

AWS SageMaker, Google Vertex AI, Azure ML

, or equivalent.

- Strong

Python programming skills.

- Familiarity with

JavaScript/TypeScript or mobile/native development is a plus.

- Strong understanding of

LLMs, prompt engineering, embeddings, RAG, and vector databases

.

- Experience with

Pinecone, FAISS, Weaviate

, or similar vector database technologies.

- Experience with

AWS, Azure, or GCP cloud platforms.

- Hands-on experience with

Docker and Kubernetes

.

- Familiarity with

MLOps, model versioning, ML CI/CD, monitoring, and observability

.

- Robust client-facing communication and presentation skills

.

- Ability to explain technical concepts to non-technical stakeholders

.

- Experience in

IT services/consulting environments is highly preferred.

- Ability to manage multiple client engagements and projects simultaneously

.

📌 AI/ML Engineer – Agentic AI (Visakhapatnam)
🏢 WNS
📍 Visakhapatnam