Job Summary
Synechron is seeking a capable and innovative GenAI Engineer to design, develop, and deploy Generative AI solutions across enterprise platforms. This role combines hands-on GenAI/NLP/model development with collaboration across product, data, and engineering teams to deliver scalable, secure, and production-ready AI-powered solutions. The ideal candidate will drive AI innovation, mentor teammates, and ensure alignment with governance, risk, and compliance requirements while delivering measurable business value.
Software Requirements
Required Skills (Essential)
Hands-on experience with Generative AI and large language models (LLMs) such as OpenAI, AWS Bedrock, or equivalent
Strong proficiency in Python for AI development, model integration, and data processing
Experience with Retrieval-Augmented Generation (RAG) pipelines and serverless or event-driven architectures (e.g., SageMaker + Lambda)
Proficiency with vector databases and embeddings (e.g., Faiss, Pinecone)
Knowledge of deploying AI models on cloud platforms (AWS, Azure, or GCP) and basic MLOps concepts
Experience with AI model governance, data privacy, and security considerations in production
Familiarity with version control (Git) and collaborative development workflows
Understanding of SDLC/ML lifecycle, experimentation, and model evaluation
Preferred
Experience with containerization (Docker) and orchestration (Kubernetes) for AI services
Exposure to CI/CD pipelines for AI workflows (GitHub Actions, Jenkins, Harness)
Knowledge of model monitoring, bias mitigation, and safety in AI systems
Experience integrating AI solutions with existing enterprise data pipelines and APIs
Familiarity with AI tooling for code generation, data labeling, or automated testing
Overall Responsibilities
Design, develop, and optimize GenAI/AI-driven solutions and autonomous AI workflows
Lead implementation, deployment, and governance of AI models within CI/CD pipelines on cloud platforms
Mentor and guide junior AI engineers, promoting best practices in AI development, MLOps, and responsible AI
Identify, evaluate, and pilot new AI technologies and architectures to improve business processes
Collaborate with product, data, and platform teams to translate business requirements into scalable AI solutions
Stay current with AI/ML trends and industry developments; translate insights into actionable plans
Ensure governance, risk, and compliance considerations are embedded in AI initiatives
Develop and maintain AI architecture, deployment guidelines, and model governance documentation
Drive continuous improvement of AI delivery, automation, and operational efficiency
Technical Skills (By Category)
Programming Languages (Essential)
Essential: Python
Preferred: R, Java, or C++ for integration or performance optimization
AI Frameworks & Libraries
Essential: PyTorch, TensorFlow, Hugging Face Transformers
Preferred: LangChain, SpaCy, OpenAI API patterns
Model Development & Deployment
Essential: Training, fine-tuning, evaluation, and deployment of LLMs; embeddings and vector-based retrieval
Preferred: Encryption layers, secure model serving, model governance practices
Cloud & Infrastructure
Essential: Experience deploying AI models on cloud platforms (AWS, Azure, GCP)
Preferred: Managed AI services (SageMaker, Vertex AI, Azure ML) and multi-cloud strategies
Data Management & Storage
Essential: Vector databases and data pipelines for AI workloads; data preprocessing
Preferred: NoSQL databases and data warehousing concepts; data lineage and governance
DevOps & MLOps
Essential: Version control (Git), CI/CD concepts, basic monitoring for AI pipelines
Preferred: Containerization (Docker), orchestration (Kubernetes), MLOps tools, model monitoring platforms
Security & Compliance
Essential: Data privacy, model security, and governance for AI deployments
Preferred: AI safety, bias detection/mitigation, and auditable model governance
Experience Requirements
4–9 years in AI/ML/Data Science with at least 3 years in GenAI/NLP
Proven track record delivering AI/ML solutions in production environments
Experience collaborating with cross-functional teams (product, data science, engineering, security)
Exposure to regulated industries and governance considerations is a plus
Alternative pathways: strong project experience, relevant certifications, or notable contributions to GenAI/NLP projects
Day-to-Day Activities
Design, train, fine-tune, and deploy GenAI/NLP models and autonomous AI components
Collaborate with product, data, and engineering teams to identify AI use cases and success metrics
Build and maintain AI pipelines (training, inference, monitoring) in cloud environments
Evaluate new AI techniques, tools, and platforms; lead proofs-of-concept
Monitor model performance, detect drift, and implement retraining or adjustments
Maintain comprehensive documentation on model architecture, data pipelines, and deployment steps
Ensure governance, risk, and compliance considerations are integrated into AI initiatives
Mentor junior AI engineers and promote knowledge sharing
Qualifications
Bachelor’s or Master’s degree in Computer Science, Data Science, AI, or related field
4–9 years of experience in AI/ML/Data Science with at least 3 years in GenAI/NLP
Certifications in AI/ML, cloud platforms, or MLOps are advantageous
Professional Competencies
Strategic thinking and analytical problem-solving for AI applications
Clear communication and stakeholder management for technical and non-technical audiences
Leadership and teamwork with the ability to mentor peers
Adaptability to evolving AI technologies and regulatory landscapes
Innovation mindset with a focus on scalable, responsible AI solutions
Time management and prioritization in a dynamic environment
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.
Candidate Application Notice
Skills Required
- Hands-on experience with Generative AI and large language models (OpenAI, AWS Bedrock, or equivalent)
- Strong proficiency in Python for AI development, model integration, and data processing
- Experience with Retrieval-Augmented Generation (RAG) pipelines and serverless/event-driven architectures (e.g., SageMaker + Lambda)
- Proficiency with vector databases and embeddings (Faiss, Pinecone)
- Experience deploying AI models on cloud platforms (AWS, Azure, or GCP) and basic MLOps concepts
- Experience with AI model governance, data privacy, and security considerations in production
- Familiarity with version control (Git) and collaborative development workflows
- Understanding of SDLC/ML lifecycle, experimentation, and model evaluation
- 4-9 years in AI/ML/Data Science with at least 3 years in GenAI/NLP
- Bachelor's or Master's degree in Computer Science, Data Science, AI, or related field
- Proven track record delivering AI/ML solutions in production environments
- Experience collaborating with cross-functional teams (product, data science, engineering, security)
- Experience with PyTorch, TensorFlow, and Hugging Face Transformers
- Containerization (Docker) and orchestration (Kubernetes) for AI services
- Exposure to CI/CD pipelines for AI workflows (GitHub Actions, Jenkins, Harness)
- Knowledge of model monitoring, bias mitigation, and safety in AI systems
- Familiarity with LangChain, SpaCy, OpenAI API patterns
- Certifications in AI/ML, cloud platforms, or MLOps
Synechron Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Synechron and has not been reviewed or approved by Synechron.
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Fair & Transparent Compensation — Pay is frequently characterized as competitive, particularly relative to large service-consulting peers and in certain in-demand skill areas. Compensation sentiment appears strongest when staffing is stable on strong client engagements and for market-aligned roles in major hubs.
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Healthcare Strength — Healthcare coverage is often portrayed as a strong point in the U.S., with broad coverage and relatively favorable out-of-pocket experiences. Core medical, dental, and vision options are consistently described as meeting or exceeding a baseline expectation for consulting roles.
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Equity Value & Accessibility — Equity was made broadly accessible through a company-wide RSU grant tied to a major revenue milestone. This is positioned as a notable upside even if it is framed as a one-time recognition event rather than an ongoing program.
Synechron Insights
What We Do
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 14,700+, and has 48 offices in 19 countries within key global markets. For more information on the company, please visit our website: www.synechron.com.







