Job Summary
Synechron is seeking a highly experienced Python Data & AI Engineer to lead the design, development, and deployment of intelligent data pipelines supporting AI/ML applications. This role involves integrating unstructured data processing, working with large-scale data storage, and supporting AI model deployment in production environments. The successful candidate will collaborate with cross-functional teams to innovate data solutions, optimize performance, and enable AI-driven insights aligned with enterprise goals.
Software Requirements
Required:
Expertise in Python (latest stable version) for data processing, automation, and ML workflows
Hands-on experience with PySpark for distributed data processing at scale
Experience with data ingestion, cleansing, and transformation for unstructured data (PDFs, emails, forms)
Familiarity with NLP and AI frameworks such as Hugging Face, Transformers, LangChain, and FAISS for semantic search and retrieval-augmented generation (RAG) systems
Knowledge of data storage solutions including NoSQL (MongoDB, DynamoDB) and relational databases (PostgreSQL, MySQL)
Experience working with cloud platforms such as AWS, Azure, or GCP for deployment and scalability
Understanding of data quality metrics, data governance, and data security best practices
Preferred:
Experience with AI/ML lifecycle management including model training, fine-tuning, prompt engineering, and inference deployment
Familiarity with containerization (Docker) and orchestration (Kubernetes) for scalable AI/ML systems
Knowledge of data orchestration tools like Apache Airflow or Prefect
Overall Responsibilities
Design, develop, and optimize scalable data pipelines for unstructured data, supporting AI/ML applications and retrieval systems
Build and integrate document classification, enrichment, and metadata tagging workflows to prepare high-quality data for model consumption
Implement and support RAG architectures supporting semantic search, question-answering, and document retrieval workflows
Engineer and manage embeddings, document chunking, and vector database integrations supporting enterprise search capabilities
Collaborate with AI architects, data scientists, and platform teams to deliver end-to-end data solutions supporting intelligent applications
Automate data ingestion, processing, and deployment workflows for efficiency and reproducibility
Conduct system performance monitoring, troubleshoot issues, and implement continuous improvements
Ensure systems adhere to security, compliance, and data governance standards
Technical Skills (By Category)
Programming Languages:
Required: Python, PySpark for distributed data processing
Preferred: SQL, Java, or Scala for integration and performance optimization
Data Management & Storage:
NoSQL (MongoDB, DynamoDB), relational databases (PostgreSQL, MySQL), data modeling, and query optimization
Cloud Technologies:
AWS, Azure, or GCP services supporting scalable data pipelines and AI/ML deployment (e.g., BigQuery, S3, Dataflow, GKE)
Frameworks & Libraries:
Hugging Face Transformers, LangChain, FAISS, Spark MLlib, NLP libraries for document understanding and retrieval
Data Orchestration & Automation:
Apache Airflow, Prefect, Terraform, Docker, Kubernetes for deployment and pipeline management
Security & Governance:
Data encryption, access controls, and compliance with enterprise security standards
Experience Requirements
Minimum of 6 years supporting data engineering, AI/ML deployment, or unstructured data processing in enterprise environments
Proven expertise in building large-scale, scalable data pipelines supporting AI workflows
Hands-on experience with vector databases, embedding models, and retrieval-augmented generation systems
Demonstrated success integrating cloud-based data systems with AI/ML models in production environments
Industry experience in financial services, healthcare, or enterprise analytics preferred but not mandatory
Day-to-Day Activities
Develop, test, and optimize data pipelines for unstructured data ingestion, cleansing, and transformation workflows
Support the development and deployment of AI models, including prompt engineering, fine-tuning, and inference workflows
Collaborate with data scientists and platform teams to design scalable, cloud-enabled AI and data solutions
Troubleshoot and resolve technical bottlenecks related to data pipelines and model deployment
Automate data workflows, manage infrastructure as code, and supports cloud migration strategies
Monitor system health, optimize data storage and processing performance, and ensure security and compliance standards are maintained
Document system architecture, data workflows, and operational procedures
Qualifications
Bachelor’s or Master’s degree in Computer Science, Data Science, or related field
6+ years supporting or developing data engineering or AI pipelines supporting enterprise applications
Certifications such as GCP Professional Data Engineer, AWS Certified Machine Learning, or equivalent are advantageous
Proven experience with unstructured data processing, vector search, and retrieval-augmented generation workflows
Professional Competencies
Strong analytical and troubleshooting skills for complex data and AI systems
Excellent communication skills to effectively engage with technical teams and stakeholders
Leadership qualities to mentor junior engineers and promote best practices in data and AI engineering
Strategic thinking to design scalable, secure, and compliant data platforms
Adaptability to new tools, frameworks, and emerging AI/ML trends
Time management and organizational skills to handle multiple projects effectively
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.