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Posted 16 June, 2026

AI Engineer

Trinity Technology Solutions LLC
Mumbai, MH, IN Full Time
Reference: bed25344a12c896a

Job Description

Job Description

Position: AI Engineer

Experience:-3–12 years

Location: Bangalore, Mumbai, Gurgaon

Key Responsibilities

 Design, build, and fine-tune machine learning, deep learning, and Generative AI

models for real-world use cases.

 Develop Agentic AI systems using frameworks such as ADK, LangGraph, or

equivalent for orchestration and reasoning.

 Build solutions leveraging LLMs, RAG pipelines, embeddings, and vector

databases.

 Design and implement AI systems for text, structured/unstructured data, and

conversational use cases.

 Apply core NLP techniques including classification, summarization, entity

recognition, and semantic search.

 Develop scalable algorithms for search, retrieval, and real-time inference.

 Build and integrate AI microservices into enterprise systems using APIs, event-

driven architectures, and cloud services.

 Deploy and operate AI workloads using Docker, Kubernetes, and managed cloud

AI platforms (Azure ML, AWS SageMaker, GCP Vertex AI).

 Optimize solutions for performance, cost, latency, and security.

 Collect, preprocess, and manage large datasets for fine-tuning and inference.

 Continuously monitor and optimize models and prompts for accuracy, scalability,

and efficiency.

 Partner with Solution Architects and business teams to translate requirements

into production-ready AI solutions.

 Champion Responsible AI practices, including fairness, bias mitigation, and

compliance.

Required Skills

 Proficiency in Python, SQL, and ML frameworks (TensorFlow, PyTorch).

 Strong understanding of Generative AI concepts (transformers, embeddings,

fine-tuning).

 Experience with Agentic AI frameworks (ADK, LangGraph, AutoGen).

 Familiarity with cloud platforms (AWS, Azure, GCP) for AI deployment.

 Knowledge of prompt engineering, vector databases (Pinecone, Weaviate), and

retrieval-augmented generation (RAG).

 Hands-on with cloud-native AI deployments (Azure, AWS, GCP).

 Familiarity with API-driven design, microservices, and event-driven architectures.

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