Job Summary
Synechron is seeking a skilled Python AI Engineer to design, develop, and deploy AI-driven solutions across enterprise platforms. This role emphasizes hands-on AI development, collaboration with data scientists and engineers, and delivering scalable, secure, production-ready models and workflows. The ideal candidate will contribute to advancing AI capabilities, mentor teammates, and ensure alignment with governance, risk, and compliance requirements while driving business value.

Software Requirements

Required Skills (Essential)

• Proficiency in Python 3.x for AI/ML development, data processing, and orchestration

  
  

• Hands-on experience with AI frameworks such as TensorFlow and PyTorch

  
  

• Experience developing and deploying machine learning models, including NLP, CV, or tabular ML, in production

  
  

• Strong knowledge of cloud platforms (AWS, Azure, or GCP) for model training, deployment, and monitoring

  
  

• Experience with data processing libraries (Pandas, NumPy) and data manipulation

  
  

• Proficiency with version control systems (Git) and collaboration platforms (GitHub, GitLab, Bitbucket)

  
  

• Familiarity with SDLC/Agile methodologies and cross-functional teamwork

  
  

• Experience designing and implementing APIs to expose AI capabilities (REST/GraphQL)

  
  

• Strong SQL knowledge and data management skills for training/validation data

  
  

• Basic understanding of data governance, privacy, and security considerations in AI

  
  

Preferred Skills

• Experience with MLOps tooling (model versioning, monitoring, retraining pipelines)

  
  

• Containerization (Docker) and orchestration (Kubernetes) for AI services

  
  

• Experience with model monitoring and bias/safety considerations

  
  

• Familiarity with data visualization or BI integrations to present AI results

  
  

• Knowledge of data pipelines, data quality, and governance in AI projects

  
  

Overall Responsibilities

• Design, develop, and deploy AI models and AI-driven solutions across business domains

  
  

• Collaborate with data scientists, software engineers, product managers, and business stakeholders to translate requirements into scalable AI solutions

  
  

• Build and optimize end-to-end ML workflows, including data ingestion, feature engineering, model training, evaluation, and deployment

  
  

• Ensure governance, risk, and compliance considerations are embedded in AI initiatives

  
  

• Mentor and coach junior AI engineers; promote best practices in AI development and MLOps

  
  

• Stay current with AI/ML trends and incorporate cutting-edge techniques into projects

  
  

• Develop and maintain documentation for model architectures, data pipelines, and deployment guidelines

  
  

• Drive continuous improvement of AI delivery, automation, and operational efficiency

  
  

Technical Skills (By Category)

Programming Languages (Essential & Preferred)

• Essential: Python

  
  

• Preferred: Additional languages such as R, Java, or Go for integration or specialized workloads

  
  

AI Frameworks & Libraries

• Essential: TensorFlow, PyTorch

  
  

• Preferred: Hugging Face transformers, spaCy, LangChain

  
  

Model Development & Deployment

• Essential: Training, evaluation, and deployment of AI models; NLP/vision capabilities as applicable

  
  

• Preferred: MLOps tooling, model monitoring platforms, bias detection, governance practices

  
  

Cloud & Infrastructure

• Essential: Cloud experience with AWS, Azure, or GCP for training, deployment, and monitoring

  
  

• Preferred: Multi-cloud deployments and cloud-native AI services

  
  

Data Management & Storage

• Essential: Data preprocessing, feature engineering, data validation, and data lineage awareness

  
  

• Preferred: Data governance concepts, data quality frameworks, data virtualization

  
  

DevOps & MLOps

• Essential: Version control (Git), CI/CD concepts, and basic monitoring for AI pipelines

  
  

• Preferred: Containerization (Docker), orchestration (Kubernetes), CI/CD tooling (GitHub Actions, Jenkins)

  
  

Security & Compliance

• Essential: Data privacy, secure model serving, and governance for AI deployments

  
  

• Preferred: PCI-DSS/HIPAA awareness and advanced security controls for AI

  
  

Experience Requirements

• 5–7 years in AI/ML/data science, with hands-on production experience in deploying ML models

  
  

• Demonstrated ability to collaborate with cross-functional teams and deliver AI-enabled solutions

  
  

• Prior experience in regulated industries or enterprise environments is advantageous

  
  

• Alternative pathways: strong project portfolio, certifications in AI/ML, or significant contributions to production AI systems

  
  

Day-to-Day Activities

• Design, train, evaluate, and deploy AI models and related workflows

  
  

• Collaborate with product, data science, engineering, and business teams to identify use cases and success metrics

  
  

• Build and maintain data pipelines and feature stores for AI models

  
  

• Monitor model performance, detect drift, and initiate retraining or updates

  
  

• Create and maintain documentation for model architecture, data flows, and deployment steps

  
  

• Participate in governance, risk, and compliance activities related to AI initiatives

  
  

• Mentor peers and share best practices in AI development and operations

  
  

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Data Science, AI, or related field

  
  

• Certifications in AI/ML, cloud platforms, or MLOps are advantageous

  
  

• Ongoing commitment to professional development in AI technologies and responsible AI practices

  
  

Professional Competencies

• Strategic thinking and analytical problem-solving for AI projects

  
  

• Clear, effective communication with technical and non-technical stakeholders

  
  

• Leadership and teamwork to guide cross-functional teams

  
  

• Adaptability to evolving AI technologies and regulatory requirements

  
  

• Innovation mindset with a focus on scalable, secure, and responsible AI solutions

  
  

• Time management and prioritization in a dynamic environment

  
  

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.

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