GENERATIVE AI • AI/ML • PYTHON • DATABRICKS

Generative Technology

AI/ML, Python, Gen AI & Databricks

Build and deliver practical AI/ML and Generative AI solutions by combining Python engineering, prompt engineering, model evaluation, MLOps and scalable data platforms in a client-facing consulting environment.

Experience: 3–5 Years

Domain: AI/ML & GenAI

Core Language: Python

Platform: Databricks

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IDEAL CANDIDATE

Who Is This Role For?

This opportunity is suited for a Python-focused AI/ML professional who can move from business requirements to working AI solutions, balancing experimentation with production readiness.

Python AI/ML Engineer

Has 3–5 years of professional experience delivering Python-based solutions with practical AI/ML or Generative AI exposure.

Generative AI Practitioner

Understands prompting, evaluation, iteration, response quality, hallucination checks, safety and consistency.

Solution-Oriented Consultant

Can understand client goals, translate them into AI use cases, define success metrics and communicate technical trade-offs.

Production-Minded Engineer

Can balance rapid prototyping with security, reliability, performance, scalability and production readiness.

ROLE OVERVIEW

From Business Problem to AI Solution

The role combines consulting, Generative AI development and AI/ML engineering. You will work with stakeholders to identify valuable use cases and contribute to designing, building, evaluating and integrating AI solutions.

Discover Understand business goals

Design Define AI solution

Build Develop with Python

Evaluate Measure AI quality

Deliver Move toward production

KEY RESPONSIBILITIES

What You Will Do

Understand Client Requirements

Partner with client stakeholders to understand business goals, translate them into AI/ML and Generative AI use cases, and define measurable success metrics.

Contribute to Solution Design

Support solution architecture, effort estimation and delivery planning for AI initiatives in a consulting environment.

Build Generative AI Solutions

Develop Python-based prototypes and production-ready components for prompting, evaluation and iterative Generative AI workflows.

Engineer Prompts & Guardrails

Develop and refine prompts, templates and guardrails to improve response quality, safety and consistency.

Evaluate AI Outputs

Implement evaluation approaches covering accuracy, relevance, hallucination checks and continuous quality improvement.

Develop ML Pipelines

Develop and maintain Python-based pipelines for data preparation, training, inference and monitoring.

Experiment & Tune Models

Perform model experimentation, feature engineering and performance tuning aligned with business requirements.

Collaborate Across Teams

Work with cross-functional teams to integrate AI services into applications, workflows and enterprise environments.

GENERATIVE AI ENGINEERING

Build, Evaluate & Improve GenAI Applications

Prompt Engineering

Create, refine and test prompts, templates and guardrails for reliable Generative AI responses.

AI Evaluation

Measure accuracy, relevance, hallucination and response quality to drive iterative improvement.

RAG Applications

Work with retrieval-augmented generation, embeddings, vector search and knowledge-based AI applications.

AI/ML ENGINEERING

Engineering the Machine Learning Lifecycle

Data Preparation

Build Python-based workflows for preparing and transforming data for machine learning applications.

Model Development

Apply supervised and unsupervised learning concepts, feature engineering and model validation.

Inference & Monitoring

Support inference pipelines and production monitoring while tracking model behavior and performance.

REQUIRED QUALIFICATIONS

What You Need

Professional Experience 3–5 years of professional experience delivering Python-based solutions, including AI/ML or Generative AI components.

Generative AI Hands-on understanding of prompt engineering, evaluation and iterative improvement.

AI/ML Fundamentals Working knowledge of supervised and unsupervised learning, model validation and performance metrics.

Python Strong programming skills with clean coding, testing and debugging practices.

Education Bachelor's degree in Engineering, Computers or Artificial Intelligence.

Consulting Exposure Client-facing AI/ML delivery experience is preferred.

PREFERRED EXPERIENCE

Skills That Strengthen Your Profile

Candidates with the following experience can bring additional value to AI solution delivery and production implementation.

RAG Embeddings Vector Databases Prompt Engineering MLOps Model Versioning Experiment Tracking CI/CD for ML Production Monitoring Databricks Tool Calling AI Agents

PRODUCTION MINDSET

From Prototype to Production

The role requires more than building prototypes. Strong candidates should understand the engineering considerations required to turn experimental AI solutions into reliable production capabilities.

Performance

Consider response time, model performance and scalable execution when designing AI solutions.

Security

Consider security requirements and responsible handling of AI services and enterprise data.

Reliability

Build maintainable solutions with testing, monitoring and production-readiness practices.

TECHNOLOGY STACK

Core Technologies & Concepts

Python AI/ML Generative AI Databricks RAG Embeddings Vector Search Prompt Engineering MLOps Model Validation AI Evaluation Tool/Function Calling

Build the Next Generation of AI Solutions

Bring your Python, AI/ML and Generative AI expertise to a role focused on solving real business problems and delivering scalable AI solutions.

Apply Now ↗