GEN AI Engineer

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.

EXL (NASDAQ: EXLS) is a leading data analytics and digital operations and solutions company. We partner with clients using a data and AI-led approach to reinvent business models, drive better business outcomes and unlock growth with speed. EXL harnesses the power of data, analytics, AI, and deep industry knowledge to transform operations for the world's leading corporations in industries including insurance, healthcare, banking and financial services, media and retail, among others. EXL was founded in 1999 with the core values of innovation, collaboration, excellence, integrity and respect. We are headquartered in New York and have more than 54,000 employees spanning six continents. For more information, visit www.exlservice.com.

EXL never requires or asks for fees/payments or credit card or bank details during any phase of the recruitment or hiring process and has not authorized any agencies or partners to collect any fee or payment from prospective candidates. EXL will only extend a job offer after a candidate has gone through a formal interview process with members of EXL's Human Resources team, as well as our hiring managers.

• 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.

• 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
• 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