GenAI SME/Architect with AWS

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 seeking an exceptional hands-on Technical Lead to spearhead our enterprise GenAI engineering program. This is a unique opportunity for a seasoned technologist who combines deep AI/ML expertise with practical engineering skills to build and operationalize cutting-edge generative AI solutions. You will lead the development of AI agents and platforms while remaining deeply involved in the technical implementation.

Key Responsibilities

Technical Leadership & Development

• Lead the design, development, and deployment of enterprise-scale GenAI solutions using a hybrid of custom developed solutions and open-source platforms (Dify, OpenWebUI, etc.)
• Architect and implement AI agents using Python frameworks including LlamaIndex and LangGraph
• Drive hands-on development while providing technical guidance to the engineering team
• Establish best practices for GenAI development, deployment, and operations

AI/ML Engineering

• Design and implement LLM-based solutions with deep understanding of model architectures, fine-tuning, and prompt engineering
• Apply classical machine learning techniques where appropriate to complement GenAI solutions
• Optimize AI pipelines for performance, cost, and scalability
• Implement RAG (Retrieval Augmented Generation) patterns and vector databases

Context Engineering & Advanced RAG

• Design and implement sophisticated context engineering strategies for optimal LLM performance
• Build advanced RAG systems including multi-hop reasoning, hybrid search, and re-ranking mechanisms
• Develop agentic RAG architectures where agents dynamically query, synthesize, and validate information
• Implement context window optimization techniques and dynamic context selection strategies
• Create self-improving RAG systems with feedback loops and quality assessment

LLM Optimization & Fine-tuning

• Lead fine-tuning initiatives for domain-specific LLMs using techniques like LoRA, QLoRA, and full fine-tuning
• Implement performance optimization strategies including quantization, pruning, and distillation
• Design and execute benchmark suites to measure and improve model performance
• Optimize inference latency and throughput for production workloads
• Implement prompt optimization and few-shot learning strategies

Platform & Infrastructure

• Design event-driven architectures for asynchronous AI processing at scale
• Build and deploy containerized AI applications using Kubernetes on AWS
• Implement AWS services (SageMaker, Bedrock, Lambda, EKS, SQS, SNS, etc.) for AI workloads
• Establish CI/CD pipelines for AI model and application deployment

Security & Governance

• Implement secure design principles for AI systems including data privacy and model security
• Establish AI security frameworks covering prompt injection prevention, model access controls, and data governance
• Ensure compliance with enterprise security standards and AI ethics guidelines
• Design audit trails and monitoring for AI system behavior

Required Qualifications

AI/ML Expertise

• Deep understanding of LLMs: Architecture, training, fine-tuning, and deployment strategies
• Context engineering proficiency: Expert-level understanding of context window management, prompt engineering, and context optimization techniques
• Advanced RAG implementation: Hands-on experience building sophisticated RAG systems with hybrid search, metadata filtering, and agentic capabilities
• Fine-tuning expertise: Proven experience fine-tuning LLMs for specific domains using modern techniques (LoRA, PEFT, etc.)
• Performance optimization: Track record of optimizing LLM inference for latency, throughput, and cost
• Classical ML proficiency: Strong foundation in traditional machine learning algorithms and applications
• Python mastery: Expert-level Python with extensive experience in ML libraries (PyTorch, TensorFlow, Pandas, NumPy)
• GenAI frameworks: Hands-on experience with LlamaIndex, LangChain, LangGraph, or similar frameworks
• Open-source GenAI platforms: Experience with Dify, OpenWebUI, or comparable platforms

Engineering Excellence

• Cloud architecture: Proven experience designing and implementing AWS solutions using multiple services
• Event-driven systems: Expertise in asynchronous, event-driven architectures for scalable AI processing
• Containerization: Advanced knowledge of Docker, Kubernetes, and container orchestration
• DevOps/MLOps: Experience with CI/CD, infrastructure as code, and ML model lifecycle management

Security & Enterprise Standards

• Secure development: Strong understanding of secure coding practices and security design patterns
• AI security: Knowledge of AI-specific security concerns (adversarial attacks, data poisoning, prompt injection)
• Enterprise integration: Experience with enterprise authentication, authorization, and compliance requirements

Leadership & Communication

• 13 years of hands-on technical experience with at least recent 5 years in AI/ML
• Proven track record of leading technical teams while remaining hands-on
• Excellent communication skills to articulate complex technical concepts to diverse stakeholders
• Experience working in enterprise environments with multiple stakeholders

Preferred Qualifications

• Experience with multi-agent systems and agent orchestration
• Knowledge of vector databases (Qdrant, OpenSearch, pgvector)
• Expertise in embedding models and semantic search optimization
• Contributions to open-source AI/ML projects
• Experience with model quantization and edge deployment
• Knowledge of graph-based RAG and knowledge graph integration
• Certifications in AWS, Kubernetes, or ML platforms

We offer:

• A highly competitive compensation and benefits package.
• A multinational organization with 58 offices in 21 countries and the possibility to work abroad.
• 10 days of paid annual leave (plus sick leave and national holidays).
• Maternity & paternity leave plans.
• A comprehensive insurance plan including medical, dental, vision, life insurance, and long-/short-term disability (plans vary by region).
• Retirement savings plans.
• A higher education certification policy.
• Commuter benefits (varies by region).
• Extensive training opportunities, focused on skills, substantive knowledge, and personal development.
• On-demand Udemy for Business for all Synechron employees with free access to more than 5000 curated courses.
• Coaching opportunities with experienced colleagues from our Financial Innovation Labs (FinLabs) and Center of Excellences (CoE) groups.
• Cutting edge projects at the world’s leading tier-one banks, financial institutions and insurance firms.
• A flat and approachable organization.
• A truly diverse, fun-loving, and global work culture.

S YNECHRON’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.