Generative AI Engineer is a hands-on technical role focused on building, deploying, and optimizing production-grade generative AI solutions. This role works closely with AI Architects, data scientists, and platform teams to translate business problems into scalable AI-driven applications using large language models and modern GenAI frameworks. The Senior AI Engineer is responsible for designing and implementing components such as prompt workflows, retrieval-augmented generation pipelines, vector search integrations, and lightweight agent-based systems, while ensuring performance, reliability, and cost efficiency in production environments. The role emphasizes strong software engineering practices, cloud-native development, and LLMOps fundamentals, including testing, monitoring, and CI/CD integration. Candidates are expected to contribute ideas, improve existing architectures, and mentor junior engineers, while operating within established architectural guardrails. This position is ideal for a practitioner who enjoys deep technical problem-solving, rapid experimentation, and delivering measurable business impact through practical, scalable generative AI solutions.
Responsibilities- Design, develop, and deploy production-grade Generative AI solutions for business use cases
- Build and maintain LLM-based applications using prompts, chains, agents, and RAG pipelines
- Implement AI components under defined solution and architectural guidelines
- Integrate LLMs with enterprise data sources, vector databases, and APIs
- Optimize model accuracy, latency, scalability, and cost in production environments
- Collaborate closely with AI Architects, data scientists, and platform engineering teams
- Apply strong software engineering practices including code reviews, testing, and documentation
- Support LLMOps activities such as model evaluation, monitoring, versioning, and CI/CD integration
- Participate in Agile delivery ceremonies including sprint planning, demos, and retrospectives
- Bachelor’s degree in Computer Science, Artificial Intelligence, Engineering, or a related field
- Master’s degree in AI, Data Science, or a related discipline is a plus
- 3-6 years of experience in software engineering, AI/ML, or data science roles
- 3+ years of hands-on experience building Generative AI or NLP-based solutions
- Demonstrated experience deploying AI / LLM-based applications into production
- Strong proficiency in Python and modern software development practices
- Practical experience working with LLM frameworks, vector databases, and RAG-based architectures
- Experience working on cloud platforms such as AWS, Azure, GCP, or Nvidia ecosystems
- Familiarity with Agile development methodologies and collaborative delivery models
- Strong problem-solving skills with the ability to translate business requirements into technical solutions
Base Compensation Range: $90-125k
The posted range is the hiring range for this role — a subset of the broader range available to employees over time — and reflects base salary across our national hiring scale. Final offers are based on several factors, including the candidate's skills and experience, internal pay equity, work location, market conditions for the role, and the specific scope and responsibilities of the position. The top of the range is reserved for candidates who notably exceed the requirements; the lower end applies to those with less experience or fewer preferred qualifications. For positions based in higher-cost zones (e.g., California, New York, New Jersey), actual compensation may exceed the posted range; your recruiter will share specifics during the process.
About UsSkills Required
- Bachelor's degree in Computer Science, AI, Engineering, or related field
- 3-6 years experience in software engineering, AI/ML, or data science roles
- 3+ years hands-on experience building Generative AI or NLP-based solutions
- Demonstrated experience deploying AI/LLM-based applications into production
- Strong proficiency in Python and modern software development practices
- Practical experience with LLM frameworks, RAG-based architectures, and vector databases
- Experience with cloud platforms (AWS, Azure, GCP, or NVIDIA ecosystems)
- Experience with LLMOps fundamentals including model evaluation, monitoring, versioning, and CI/CD integration
- Familiarity with Agile development methodologies and collaborative delivery models
- Master's degree in AI, Data Science, or related discipline
What We Do
Choosing a digital partner is about more than capabilities — it’s about collaboration and character. Unrealistic overhauls and off-the-shelf products ignore what matters most — your unique needs, culture, goals, and your legacy data and technology environments. At EXL, our collaboration is built on ongoing listening and learning to adapt our methodologies. We’re your business evolution partner—tailoring solutions that make the most of data to make better business decisions and drive more intelligence into your increasingly digital operations. Whether your goals are scaling the use of AI and digital, redesign operating models, or driving better and faster decisions, we’re here to partner with you to help you gain—and maintain—competitive advantage with efficient, sustainable models at scale. Our expertise in transformation, data science, and change management helps make your business more efficient and effective, improve customer relationships and enhance revenue growth. Instead of focusing on multi-year, resource- and time-intensive platform designs or migrations, we look deeper at your entire value chain to integrate strategies with impact. We use our specialization in analytics, digital interventions, and operations management—alongside deep industry expertise — to deliver solutions that help you outperform the competition. At EXL, it’s all about outcomes—your outcomes—and delivering success on your terms. Share your goals with us and together, we’ll optimize how you leverage data to drive your business forward. For more information, visit www.exlservice.com.
