Python: needed to build automation, AI workflows, and data processing logic.
Machine learning basics: needed for classification, anomaly detection, and smart matching.
Ollama / local model integration: needed for AI features without external LLM access
API integration: needed to connect systems and automate data exchange
SQL: needed for data validation, reconciliation, and report checks
OCR: extracting structured information from documents and images
Debugging and logging: needed to quickly identify issues and maintain traceability
FastAPI or similar backend skills: useful for building AI and automation APIs
Git Version control
Good-to-Have Skills
Financial /reporting domain knowledge
Exposure to test Automation: beneficial when collaborating with QA team.
Docker and CI/CD: useful for packaging and deploying solutions
Experience with audit trails and compliance testing: important for controlled enterprise workflows
Text classification and anomaly detection: useful for AI-supported testing and data checks
Vector search or retrieval-based solutions(RAG): useful if document search is needed later
QA and validation skills: needed to confirm output accuracy and business correctness
Tech Stack
Python
FastAPI
Ollama
Open-source LLMs
SQL
Pandas and NumPy
scikit-learn
OCR tools such as Tesseract, Azure Form Recognizer, AWS Textract, or Google Document AI
Docker
Git and CI/CD pipelines
REST APIs and JSON integration
Vector database for document search and retrieval
RAG
The resource should possess strong AI/ML engineering skills and be capable of developing AI-powered solutions while collaborating closely with QA and business teams to ensure solution quality, accuracy, and enterprise readiness. Prior exposure to automation testing is an added advantage but is not mandatory.
Mandatory Competencies
Data AI - GEN AI - Python
Data AI - GEN AI - NumPy
Data AI - GEN AI - Pandas
Data AI - GEN AI - Workflow Agentic Frameworks (LangChain / LangGraph)
Data AI - GEN AI - Prompt Engineering / Vector Databases
Data AI - GEN AI - Fine tuning Model Customization / AI Agents Tool Calling
Data AI - GEN AI - Azure OpenAI Service
Data AI - GEN AI - Advanced GenAI Agentic Framework Concepts
Data AI - GEN AI - Cloud Application Integration Deployment
Job Classification
Industry: IT Services & ConsultingFunctional Area / Department: Engineering - Software & QARole Category: Software DevelopmentRole: Search EngineerEmployement Type: Full time