Job Summary
Synechron is seeking an experienced AI/ML Data Engineer specialized in processing unstructured data and integrating advanced language models within enterprise environments. This role involves designing scalable data pipelines, implementing document cleansing, classification, and enrichment, and supporting Retrieval-Augmented Generation (RAG) architectures. The successful candidate will bridge data engineering and AI development to enable intelligent, AI-first applications that enhance decision-making and operational efficiency.
Software Requirements
Required:
Strong proficiency in Python (latest stable version) for building data pipelines and implementing ML workflows
Hands-on experience with PySpark for distributed data processing and large-scale ETL workflows
Experience processing unstructured data such as PDFs, texts, emails, and forms, including OCR and NLP techniques
Familiarity with NLP frameworks and libraries such as Transformers, Hugging Face, LangChain, and FAISS
Working knowledge of vector databases such as Redis or similar for semantic search and retrieval
Understanding of LLM lifecycle management, including fine-tuning, inference, and prompt engineering
Experience working with CI/CD practices, Git, and version control tools for data projects
Preferred:
Experience with cloud platforms like GCP, AWS, or Azure, supporting data pipeline deployment
Knowledge of data quality metrics and data governance best practices
Exposure to data orchestration tools such as Apache Airflow or Prefect
Overall Responsibilities
Build and maintain scalable, robust data pipelines for unstructured content, ensuring high data quality and performance efficiency
Develop algorithms for document classification, cleansing, and enrichment to feed AI/ML systems
Integrate data workflows with LLM pipelines supporting RAG architectures for semantic search and Question-Answering (QA) systems
Engineer and optimize vector embeddings, document chunking, and metadata tagging for AI applications
Collaborate closely with AI architects, data scientists, and platform teams to design end-to-end AI solutions
Implement automation, monitoring, and security best practices to ensure system reliability and compliance
Support project lifecycle activities, including proof-of-concept, testing, deployment, and ongoing monitoring
Share domain expertise, conduct knowledge sharing, and mentor team members
Technical Skills (By Category)
Programming Languages:
Required: Python, PySpark
Preferred: SQL, Java, or other scripting languages for automation and integrations
Databases & Data Management:
NoSQL (Redis, MongoDB), relational databases (PostgreSQL, MySQL), data tagging, and metadata management
Cloud Technologies:
GCP (BigQuery, Dataflow), AWS, or Azure for deployment, scaling, and storage support (preferred)
Frameworks & Libraries:
Transformers, Hugging Face, LangChain, FAISS, Spark MLlib, NLP libraries
Development & Orchestration Tools:
Git, Jenkins, CI/CD pipelines, Apache Airflow or Prefect (preferred)
Operational & Security Tools:
Monitoring platforms (Datadog, Prometheus), security best practices, data encryption
Experience Requirements
Minimum of 6 years of professional experience in data engineering, with at least 2 years dedicated to unstructured data processing and AI/ML integration
Proven success building scalable data pipelines supporting NLP, document classification, and semantic search
Hands-on experience with vector databases, embedding models, and retrieval systems supporting RAG workflows
Experience working with cloud platforms and performing data quality audits in enterprise environments
Industry experience in financial services, healthcare, or enterprise AI applications is advantageous
Day-to-Day Activities
Design, develop, and enhance data pipelines for unstructured data ingestion, processing, and enrichment
Implement NLP models, document classification, and semantic search capabilities supporting RAG architectures
Collaborate with data scientists, platform engineers, and stakeholders to address data and AI system needs
Troubleshoot data pipeline issues, optimize query performance, and implement best practices for data security and governance
Automate data workflows, manage infrastructure as code, and support cloud deployment strategies
Monitor pipeline performance, ensure data quality, and document architecture and operational workflows
Qualifications
Bachelor’s or Master’s degree in Computer Science, Data Science, or a related field
At least 6 years of experience in data engineering, focusing on unstructured data and AI model integration
Strong expertise with Python, PySpark, NLP, and vector retrieval systems
Certifications in cloud platforms or data engineering tools are preferred
Proven ability to deliver high-quality, scalable, and secure data solutions in enterprise settings
Professional Competencies
Strong analytical and troubleshooting skills for complex data and AI systems
Effective communication skills to interface with technical and business stakeholders
Leadership qualities to mentor team members and promote best practices in data engineering and AI
Strategic thinking to design scalable, secure, and compliant AI data pipelines
Adaptability to new tools, frameworks, and emerging AI/ML trends
Time management skills to prioritize tasks and deliver solutions efficiently
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.