Accolite

AI Engineer

Posted On

Oct. 7, 2025

Location

Gurugram, Haryana

Experience Level

5 - 10 Years Exp.

Job Type

Full Time

Apply By

Feb. 7, 2026

Job Description

Position Summary

We are seeking an experienced AI Engineer to spearhead AI adoption initiatives and drive engineering efficiency across our organization. This role combines deep technical expertise in generative AI with strategic thinking to accelerate AI integration, establish best practices, and mentor engineering teams in implementing scalable AI solutions. The ideal candidate will serve as both a technical leader and AI evangelist, working closely with cross-functional teams to unlock productivity gains and innovation opportunities.

Key Responsibilities

AI Strategy & Adoption

AI Tools Integration: Drive organization-wide AI adoption strategy, focusing on tools that enhance delivery speed and code quality such as GitHub Copilot, AI-powered testing frameworks, and automated documentation systems
Development Workflow Optimization: Partner with engineering teams to identify bottlenecks in delivery processes and implement AI solutions for code generation, automated testing, and deployment optimization
Productivity Metrics: Establish and track metrics for AI tool adoption impact on development velocity, code quality, and delivery timelines
ROI Assessment: Establish metrics and KPIs to measure AI implementation success and continuously optimize for maximum business impact

Technical Architecture & Implementation

RAG System Excellence: Design, implement, and maintain enterprise-grade Retrieval Augmented Generation (RAG) architectures with focus on scalability, performance, and reliability
Data Pipeline Engineering: Architect robust data transformation pipelines to migrate and optimize data from legacy systems into AI-ready formats
AI-Powered Development Tools: Implement and optimize AI tools for code generation, testing, debugging, and documentation to accelerate development cycles
Model Integration: Seamlessly integrate large language models (LLMs) and generative AI capabilities into existing software applications and workflows

Engineering Excellence & Mentorship

AI-Driven Development Practices: Establish and champion the use of AI tools for software development including code generation, automated testing, code review assistance, and technical documentation
Delivery Acceleration: Implement AI solutions that streamline development workflows, reduce manual tasks, and accelerate time-to-market for software products
Prompt Engineering Leadership: Develop sophisticated prompt engineering frameworks and train teams on effective prompt design strategies for development and operational tasks
Technical Mentorship: Provide guidance and support to engineering teams adopting AI technologies, reducing learning curves and implementation friction
Quality Assurance: Implement comprehensive testing, monitoring, and validation frameworks for AI systems

Innovation & Continuous Improvement

Development Tool Evaluation: Research and evaluate emerging AI-powered development tools, code generation platforms, and automation solutions for potential organizational adoption
Delivery Process Enhancement: Continuously identify opportunities to apply AI for improving software delivery processes, from requirements analysis to deployment and monitoring
Stakeholder Communication: Present technical concepts, productivity improvements, and project updates to both technical and non-technical stakeholders

Required Qualifications

Education & Experience

Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or related technical field
7+ years of software engineering experience
2+ years in a technical leadership or mentorship role
1+ years of hands-on experience with Generative AI, Large Language Models, and Agentic AI systems

Technical Expertise

Programming Proficiency: Expert-level programming with Python & Java//C#
Generative AI Mastery: Deep understanding of LLMs, transformer architectures, and generative AI applications (GPT-4, Claude, Llama, etc.)
Vector Databases: Experience with vector databases and semantic search technologies (Chroma, Pinecone, Weaviate)
Expertise in Scikit / Pytorch & FastAPI/Flask

AI/ML Specializations

RAG Architecture: Proven experience designing and implementing production RAG systems
Prompt Engineering: Advanced skills in prompt design, optimization, and systematic prompt engineering methodologies
NLP/NLU: Strong foundation in natural language processing and understanding techniques

Preferred Qualifications

Advanced Technical Skills

Experience with AI orchestration frameworks (LangChain, LlamaIndex, Haystack)
Knowledge of model serving and deployment platforms (MLflow, Kubeflow, Azure ML)
Familiarity with AI safety, responsible AI practices, and model interpretability
Experience with multimodal AI systems and computer vision applications

Leadership & Communication

Track record of successfully leading technical initiatives and driving adoption
Experience presenting to C-level executives and technical stakeholders
Strong project management skills with ability to coordinate cross-functional teams
Contributions to AI/ML open-source communities or technical publications

Industry Knowledge

Understanding of AI governance, ethics, and regulatory considerations
Experience with enterprise software development and deployment practices
Knowledge of UX/UI principles for AI-powered applications
Familiarity with DevOps and MLOps best practices

What We Offer

Opportunity to shape AI strategy and implementation across the organization
Access to cutting-edge AI technologies and substantial computing resources
Collaborative environment with top-tier engineering and product teams
Professional development budget for conferences, certifications, and continued learning
Competitive compensation package including equity participation

Success Metrics

Measurable increase in development velocity and code quality through AI tool adoption
Reduced time-to-market for software products through AI-enhanced development processes
Successful implementation of AI-powered development workflows across engineering teams
Demonstrated ROI from AI tools in terms of reduced development cycles and improved delivery efficiency
Effective knowledge transfer and skill development in AI-assisted development practices

This role is perfect for a technical leader who is passionate about AI's transformative potential and excited to drive meaningful change across an entire engineering organization

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