Ai Ml Engineer

Durus Consulting; Hyderabad, Chennai District, Bengaluru; On-site; INR 1,500,000 - 2,100,000; Full time

Job summary

Durus Consulting seeks an experienced AI/ML Engineer in Hyderabad to design, develop, and deploy scalable AI/ML solutions. The role focuses on GenAI capabilities, LLMs, and production‑grade architectures, with hands‑on work across Databricks, AWS Bedrock, and multi‑agent systems.

You will collaborate with data engineers and software teams to translate business requirements into robust AI/ML systems, ensure governance and monitoring, and deliver enterprise‑grade GenAI applications.

Qualifications

• Strong fundamentals and hands‑on experience in Machine Learning and Artificial Intelligence.
• Experience deploying ML models in production environments.
• Strong understanding of ML algorithms, model evaluation, feature engineering, and ML lifecycle management.
• Strong programming skills in Python.

Responsibilities

• Design, develop, and deploy scalable AI/ML solutions.
• Develop and productionize Generative AI applications using foundation models and LLMs.
• Work hands‑on with AWS Bedrock and Bedrock Agents to build GenAI solutions.
• Design and implement multi‑agent architectures and orchestration frameworks.
• Develop AI/ML pipelines and solutions using Databricks.
• Apply machine learning techniques including model development, evaluation, optimization, and deployment.
• Integrate LLMs and AI agents with enterprise data, APIs, applications, and workflows.
• Establish practices for model monitoring, governance, and responsible AI.

Skills

AI/ML Fundamentals

Production ML

ML Algorithms

Python

GenAI

LLMs

Databricks

AWS Bedrock

Multi-Agent Systems

Tools

Databricks

MLflow

Bedrock

Bedrock Agents

Job description

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.
• Strong 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.