Job Summary

We are looking for a highly skilled AI/ML Engineer with a strong background in Machine Learning and hands-on experience in Generative AI, AWS Bedrock, Bedrock Agents, Multi-Agent Orchestration, and Databricks.

The ideal candidate will have experience designing, developing, and deploying scalable AI/ML solutions and working with modern Generative AI architectures. This role will focus primarily on AI/ML and GenAI capabilities, rather than recommendation engines, player recommendation systems, or propensity modelling.

Experience with AI Governance will be an added advantage.

Key Responsibilities

- Design, develop, and deploy scalable AI/ML solutions addressing complex business problems.
- Develop and productionize Generative AI applications using foundation models, LLMs, and related frameworks.
- Work hands-on with AWS Bedrock and Bedrock Agents to build enterprise-grade GenAI solutions.
- Design and implement multi-agent architectures and orchestration frameworks for complex AI workflows.
- Develop AI/ML pipelines and solutions using Databricks and associated data/ML capabilities.
- Apply machine learning techniques including model development, evaluation, optimization, and deployment.
- Integrate LLMs and AI agents with enterprise data, APIs, applications, and business workflows.
- Implement appropriate approaches for prompt engineering, retrieval-augmented generation (RAG), model evaluation, and GenAI application development.
- Collaborate with data engineers, software engineers, architects, and business stakeholders to translate requirements into AI/ML solutions.
- Establish appropriate practices for model monitoring, performance evaluation, scalability, reliability, and responsible AI.
- Contribute to the design and implementation of AI governance, security, compliance, and responsible AI practices.
- Stay current with emerging developments in ML,



GenAI, LLMs, agentic AI, and AI/ML platforms.

Primary Skills

Strong AI/ML Background

- Strong fundamentals and hands-on experience in Machine Learning and Artificial Intelligence.
- Experience developing and deploying ML models in real-world/production environments.
- Robust understanding of ML algorithms, model evaluation, feature engineering, and ML lifecycle management.
- Strong programming skills in Python and experience with relevant ML/AI frameworks.

Generative AI

- Hands-on experience building Generative AI / LLM-based applications.
- Experience with LLM application development, prompt engineering, RAG, embeddings, vector databases, and model evaluation.
- Understanding of LLM architecture, limitations, performance optimization, and production deployment.

AWS Bedrock & Bedrock Agents

- Hands-on experience with Amazon Bedrock.
- Experience working with Bedrock Agents and integrating foundation models into enterprise applications.
- Understanding of model selection, inference, orchestration, guardrails, and enterprise GenAI architecture on AWS.

Multi-Agent Orchestration

- Experience designing and implementing multi-agent / agentic AI systems.
- Understanding of agent-to-agent communication, task decomposition, tool/function calling, workflow orchestration, and agent coordination.
- Experience with one or more agent orchestration frameworks is desirable.

Databricks

- Strong hands-on experience with Databricks for data engineering, ML,



and/or AI workloads.
- Experience with ML pipelines, model development/deployment, experiment tracking, and production ML workflows on Databricks.
- Familiarity with MLflow and the broader Databricks ML/AI ecosystem is desirable.

Secondary Skills

AI Governance

- Understanding of AI Governance, Responsible AI, and AI risk management.
- Exposure to model governance, explainability, transparency, security, privacy, and compliance considerations.
- Awareness of governance requirements for enterprise GenAI and agentic AI applications.
- Experience implementing AI guardrails, monitoring, evaluation, and governance frameworks is a plus.

Good to Have

- Experience with AWS cloud services and cloud-native AI/ML architectures.
- Experience with LLM evaluation and observability.
- Experience with vector databases and RAG architectures.
- Knowledge of MLOps/LLMOps practices.
- Experience with AI security and GenAI guardrails.
- Familiarity with open-source LLMs and frameworks.
- Experience building enterprise-scale AI/ML platforms and solutions.

What We Are Looking For The primary focus of this role is strong AI/ML capability and hands-on Generative AI engineering experience. Candidates should demonstrate practical experience in:

AI/ML GenAI/LLMs AWS Bedrock & Bedrock Agents Multi-Agent Orchestration Databricks

Experience specifically in recommendation engines, player recommendation, or propensity modelling is not a key requirement for this role.

Experience

- Typically 5+ years of experience in AI/ML, Data Science, Machine Learning Engineering, or a closely related field.
- Strong hands-on experience delivering AI/ML solutions in production environments.
- Relevant experience with GenAI, AWS Bedrock, agentic AI, and Databricks is strongly preferred.

📌 Ai Ml Engineer (Bengaluru)
🏢 Durus consulting
📍 Bengaluru