Principal AI Engineer

We are Synechron, a global consulting firm that uses digital technology to transform businesses. Our services span AI, Consulting, Digital, Cloud & DevOps, Data, and Software Engineering and we serve a range of financial and technology clients.

Role Overview

This role is for a Lead/Principal AI Engineer to design, develop, and deploy advanced AI and LLM‑powered solutions in a regulated enterprise environment. The engineer will architect scalable, secure, production‑ready AI systems that align with corporate technology standards, governance and compliance requirements.

Responsibilities

• Lead the architecture, design and implementation of enterprise‑grade AI solutions leveraging large language models and related AI technologies.
• Design and deploy LLM‑based applications using platforms such as Amazon Bedrock, Azure OpenAI, and direct model/API integrations.
• Build scalable orchestration layers for prompt execution, model routing, completion handling, response optimization and service resiliency.
• Design and implement retrieval‑augmented generation (RAG) frameworks to support enterprise search, reasoning and decision‑support use cases.
• Architect and develop AI‑powered document ingestion, conversion, parsing, extraction and analysis pipelines.
• Transform large volumes of complex, unstructured enterprise and financial documents into structured data suitable for downstream AI reasoning and business process automation.
• Design and optimize data pipelines and ETL processes for efficient ingestion, enrichment, indexing and retrieval of enterprise content.
• Design and develop backend services using Python, Node.js, Java and modern enterprise integration patterns.
• Build and maintain RESTful APIs, microservices and distributed application components supporting AI‑enabled products and services.
• Partner with user‑experience and frontend engineering teams to support AI‑enabled interfaces built with React, Angular, TypeScript, JavaScript, HTML5 and CSS3.
• Design and implement data solutions utilizing MongoDB, Azure Data Services and Azure AI Search.
• Enable intelligent document indexing, metadata extraction, semantic retrieval and enterprise‑wide search capabilities.
• Establish observability and monitoring frameworks for AI systems, covering pipeline health, model performance, latency, usage, quality and cost metrics.
• Ensure AI platforms and services comply with enterprise security, privacy, governance, risk and regulatory oversight requirements.
• Build systems with auditability, traceability, explainability and operational transparency suitable for regulated environments.

Requirements

• Bachelor’s degree in Computer Science, Engineering, Information Systems or a related technical discipline; advanced degree preferred.
• Extensive experience designing, developing and deploying production‑grade AI/ML or LLM‑based systems in enterprise environments.
• Demonstrated hands‑on expertise with Amazon Bedrock, Azure OpenAI and/or direct integration with LLM APIs and model services.
• Strong experience designing RAG architectures, prompt engineering workflows and LLM service orchestration layers.
• Proven experience in AI pipeline engineering, including document ingestion, transformation, structured extraction and downstream AI consumption.
• Strong programming expertise in Python with additional experience in Node.js and/or Java.
• Experience building and integrating REST APIs, microservices and cloud‑native services.
• Strong knowledge of ETL processes, data engineering concepts, database design and enterprise integration patterns.
• Hands‑on experience with MongoDB, Azure Data Services and Azure AI Search.
• Familiarity with modern frontend technologies including React, Angular, TypeScript, JavaScript, HTML5 and CSS3.
• Solid understanding of scalability, security, performance optimisation and enterprise software design principles.
• Experience developing solutions in regulated environments, preferably within financial services, banking, lending or compliance‑driven organisations.
• Preferred: Advanced degree in Computer Science, Artificial Intelligence, Data Science or related field.
• Experience delivering AI solutions for financial services compliance, risk management, lending operations or governance functions.
• Familiarity with enterprise frameworks for AI risk management, model governance and responsible AI practices.
• Experience implementing observability and evaluation frameworks for LLM applications in production.
• Knowledge of secure cloud deployment models across Azure and/or AWS enterprise ecosystems.
• Demonstrated success leading complex technical initiatives and influencing architecture decisions across multiple teams.

Benefits

• Competitive compensation and benefits package.
• Multinational organisation with 60 offices in 20 countries and opportunities to work abroad.
• 10 days of paid annual leave (plus sick leave and national holidays).
• Maternity and paternity leave plans.
• Comprehensive insurance plan including medical, dental, vision, life insurance and disability plans that vary by region.
• Retirement savings plans.
• Higher education certification policy.
• Commuter benefits that vary by region.
• Extensive training opportunities focused on skills, substantive knowledge and personal development.
• On‑demand access to Udemy for Business and free curated courses for all employees.
• Coaching opportunities with experienced colleagues from FinLabs and CoE groups.
• Cutting‑edge projects at leading tier‑one financial institutions and insurers.
• Flat and approachable organisational culture with a diverse, global work community.

Diversity & Inclusion Statement

We are proud to be an equal‑opportunity workplace and an affirmative action employer. We encourage applicants from all backgrounds and identities to apply. All employment decisions are based on business needs and qualifications, without regard to protected characteristics.

Sustainability & Health & Safety Standards

All positions are required to adhere to our sustainability and health‑safety standards, supporting environmental stewardship, workplace safety and sustainable practices.