Generative AI Engineer

We are

At Synechron, we believe in the power of digital to transform businesses for the better. Our global consulting firm combines creativity and innovative technology to deliver industry-leading digital solutions. Synechron’s progressive technologies and optimization strategies span end-to-end Artificial Intelligence, Consulting, Digital, Cloud \& DevOps, Data, and Software Engineering, servicing an array of noteworthy financial services and technology firms. Through research and development initiatives in our FinLabs we develop solutions for modernization, from Artificial Intelligence and Blockchain to Data Science models, Digital Underwriting, mobile-first applications and more. Over the last 20\+ years, our company has been honored with multiple employer awards, recognizing our commitment to our talented teams. With top clients to boast about, Synechron has a global workforce of 14,500\+, and has 58 offices in 21 countries within key global markets.

Our challenge

We are looking for a skilled and production-focused Lead Gen AI Engineer to join our team. In this role, candidate will design, build, and deploy generative AI-powered applications and systems, integrating large language models, RAG architectures, and agentic frameworks into production-grade products that deliver measurable business value. Candidate will work cross-functionally with product, data, and infrastructure teams to build AI capabilities that give our organization a sustainable and compounding competitive advantage.

The Role

Responsibilities:

• Design and build production LLM-powered applications and API integrations.
• Implement RAG pipelines and vector database systems for enterprise AI.
• Develop agentic AI workflows using LangChain and equivalent frameworks.
• Fine-tune and evaluate foundation models for domain-specific use cases.
• Deploy AI systems to production with observability and guardrail infrastructure.
• Optimize LLM inference performance, cost, and output quality continuously.

Required skills and qualifications

• Degree in Computer Science, Software Engineering, or related technical discipline.
• 3 to 8 years of software engineering experience with 1 to 3 years in Gen AI development.
• Proficient in Python and hands-on LLM API integration across multiple model providers.
• Strong experience with RAG architecture, vector databases, and semantic search systems.
• Familiar with agentic AI frameworks, MLOps deployment, and AI system monitoring.

Preferred Qualifications

• Experience with model fine-tuning using LoRA, QLoRA, or equivalent PEFT techniques.
• Knowledge of AI safety, output guardrails, and responsible AI deployment practices.
• Contributions to open-source AI projects or published Gen AI engineering work preferred.
• Exposure multimodal AI systems including vision, audio, and document AI applications.
• Familiar with AI governance frameworks and enterprise AI compliance requirements.

Key Skills

• LLM Application Development and API Integration
• RAG Architecture and Vector Database Engineering
• Agentic AI Framework Development
• MLOps and AI Production Deployment
• Model Fine-tuning and Evaluation

SYNECHRON’S DIVERSITY \& INCLUSION STATEMENT

Diversity \& Inclusion are fundamental to our culture, and Synechron is proud to be an equal opportunity workplace and is an affirmative action employer. Our Diversity, Equity, and Inclusion (DEI) initiative ‘Same Difference’ is committed to fostering an inclusive culture – promoting equality, diversity and an environment that is respectful to all. We strongly believe that a diverse workforce helps build stronger, successful businesses as a global company. We encourage applicants from across diverse backgrounds, race, ethnicities, religion, age, marital status, gender, sexual orientations, or disabilities to apply. We empower our global workforce by offering flexible workplace arrangements, mentoring, internal mobility, learning and development programs, and more. All employment decisions at Synechron are based on business needs, job requirements and individual qualifications, without regard to the applicant’s gender, gender identity, sexual orientation, race, ethnicity, disabled or veteran status, or any other characteristic protected by law.