Principal 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 16,700+, and has 57 offices in 22 countries within key global markets. Our challenge We are seeking a highly experienced Lead / Principal AI Engineer to lead the design, development, and deployment of advanced AI and large language model (LLM)-powered solutions within a regulated enterprise environment. This role will be responsible for architecting and delivering scalable, secure, and production-ready AI systems that align with enterprise technology standards, governance frameworks, and compliance requirements. Additional Information* The base salary for this position will vary based on geography and other factors. In accordance with law, the base salary for this role if filled within Dallas, TX is $140k - $150k/year & benefits (see below). The Role 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 that enable 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 technologies such as React, Angular, TypeScript, JavaScript, HTML5, and CSS3. Design and implement data solutions utilizing technologies such as 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, including pipeline health, model performance, latency, usage, quality, and cost metrics. Ensure AI platforms and services comply with enterprise requirements related to security, privacy, governance, risk, and regulatory oversight. Build systems with strong support for auditability, traceability, explainability, and operational transparency, particularly in 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 retrieval-augmented generation (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. Strong understanding of scalability, security, performance optimization, and enterprise software design principles. Experience developing solutions in regulated environments, preferably within financial services, banking, lending, or compliance-driven organizations. Preferred, but not required: Advanced degree in Computer Science, Artificial Intelligence, Data Science, or a 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. We offe