Executive

• Monthly Tax compliance (Data Extraction, Calculation and Filing), Tax Verification and Tax Adjustments
• Perform Activities within timelines and make sure deliverables meet the predefined KPIs
• Preparation and posting of Journal entries – Adjustments, re-classes etc.
• Perform reconciliation of Balance Sheets accounts, Cash, Tax, Sub-Ledger etc.
• Perform expense Allocations, Re-class entries, Book Adjustments and Accrual entries
• Complete all close related tasks assigned on timely basis adhering to the business quality
• Should have experience in managing a small team - **Applicable only for Senior analysts**

Senior Executive

DevOps Engineer

• Define and own the **DevSecOps and AI Security strategy**, roadmap, and operating model aligned to business and regulatory needs.
• Act as a senior advisor to engineering, platform, AI, and product leaders on **secure architecture and risk trade-offs.**
• Build and scale high-performing DevSecOps and AppSec teams; mentor other team members.
• Represent security in executive forums, client discussions, audits, and risk reviews.
• Lead security integration across **CI/CD pipelines** using Jenkins, GitHub/GitHub Actions, and similar tooling.
• Establish enterprise standards for:
• Secure build pipelines
• Secrets management
• IaC security (Terraform / CloudFormation)
• Dependency and supply-chain security
• Drive adoption of automated security controls: **SAST, DAST, SCA, API security, container scanning.**
• Oversee application security programs including threat modeling, secure design reviews, and vulnerability management.
• Monitor and improve the daily operations and BAU activities.
• Establish guardrails for **AI/GenAI solutions**, including LLM-based apps, RAG pipelines, and agentic workflows.
• Assess and mitigate risks such as prompt injection, data leakage, insecure integrations, model abuse, and third-party AI risk.
• Embed AI security controls into DevSecOps/MLOps pipelines (MLSecOps).
• Translate regulatory and client security requirements into **practical engineering controls.**
• Own security metrics, risk reporting, control evidence, and audit readiness.

Lead Security Engineer – DevSecOps

• Prior experience in all Accounts Payable functions, including Vendor Maintenance, Invoice Processing, Exception handling, Payments & reporting activities of the Accounts Payable
• Processing NON PO/PO Invoices. Enter time-sensitive Utility invoices and research any past due amounts to ensure for current accounts
• Payment processing
• Vendor Master Maintenance
• Vendor Reconciliations
• To ensure SLA targets are achieved
• Month-end responsibilities include ensuring that all invoices are processed by month-end
• Ability to comprehend complex information quickly & respond with clear solutions

Senior Executive – P2P Invoice Processing

Data Engineer

• Lead the design of enterprise-grade GenAI and agentic architectures (single-agent, multi-agent, tool-driven systems).
• Define reference architectures, reusable frameworks, and best practices for LLM applications across the organization.
• Architect and oversee implementation of end-to-end RAG pipelines: Data ingestion → chunking → embeddings → vector search → orchestration → response synthesis.
• Drive scalability, reliability, cost optimization, and performance across GenAI platforms.
• Provide technical leadership in prompt engineering, prompt orchestration, and agent workflows.
• Mentor and guide architects, engineers, and data scientists.

Principal Architect, AI Data Engineer

• Define and lead end-to-end architecture for enterprise GenAI platforms and use cases
• Design scalable agentic systems (single-agent, multi-agent, orchestration frameworks)
• Establish reference architectures, design patterns, and reusable frameworks
• Lead architecture decisions on RAG vs fine-tuning vs hybrid approaches
• Conduct technology evaluations (LLMs, vector DBs, orchestration frameworks) and recommend best-fit solutions
• Design and implement complex agentic workflows with tool calling, function orchestration, and memory strategies
• Build enterprise-grade RAG pipelines with strong focus on retrieval accuracy and evaluation
• Drive prompt architecture standards (prompt libraries, chaining, orchestration governance)
• Optimise solutions for latency, cost, scalability, and reliability
• Lead development of GenAI platforms, APIs, and microservices (FastAPI, Flask, etc.)
• Define engineering best practices: coding standards, testing, packaging, observability
• Ensure seamless integration with enterprise data platforms, APIs, and business applications
• Collaborate with MLOps teams for CI/CD, deployment pipelines, versioning, and monitoring
• Define and enforce LLM guardrails (hallucination control, safety filters, policy enforcement)
• Implement evaluation frameworks (RAG evaluation, prompt testing, benchmarking)
• Ensure compliance with data security, privacy, and enterprise governance standards
• Drive adoption of Responsible AI practices (bias mitigation, explainability, auditability)
• Partner with Data Engineering teams on Data ingestion, pipelines, and quality controls

Architect, AI Data Engineer

• Define and lead end-to-end architecture for enterprise GenAI platforms and use cases
• Design scalable agentic systems (single-agent, multi-agent, orchestration frameworks)
• Establish reference architectures, design patterns, and reusable frameworks
• Lead architecture decisions on RAG vs fine-tuning vs hybrid approaches
• Conduct technology evaluations (LLMs, vector DBs, orchestration frameworks) and recommend best-fit solutions
• Design and implement complex agentic workflows with tool calling, function orchestration, and memory strategies
• Build enterprise-grade RAG pipelines with strong focus on retrieval accuracy and evaluation
• Drive prompt architecture standards (prompt libraries, chaining, orchestration governance)
• Optimize solutions for latency, cost, scalability, and reliability
• Lead development of GenAI platforms, APIs, and microservices (FastAPI, Flask, etc.)
• Define engineering best practices: coding standards, testing, packaging, observability
• Ensure seamless integration with enterprise data platforms, APIs, and business applications
• Collaborate with MLOps teams for CI/CD, deployment pipelines, versioning, and monitoring
• Define and enforce LLM guardrails (hallucination control, safety filters, policy enforcement)
• Implement evaluation frameworks (RAG evaluation, prompt testing, benchmarking)
• Ensure compliance with data security, privacy, and enterprise governance standards
• Drive adoption of Responsible AI practices (bias mitigation, explainability, auditability)

• Architect enterprise-grade agentic and LLM solutions (single-agent, multi-agent, tool-driven workflows)
• Define scalable GenAI system design patterns (RAG, orchestration layers, evaluation frameworks)
• Act as the technical anchor for GenAI initiatives across projects
• Drive design reviews, architecture governance, and best practices
• Design and build agentic systems using LLMs for use cases such as knowledge assistants, document automation & intelligence, workflow orchestration
• Implement advanced prompt engineering strategies, prompt orchestration, and reasoning chains
• Build tool-calling / function-calling frameworks for agent workflows
• Lead end-to-end implementation of RAG pipelines: Data ingestion → chunking → embeddings → vector indexing → retrieval → response generation
• Optimise retrieval quality (recall, relevance, grounding)
• Evaluate and benchmark different architectures
• Develop production-grade APIs/services (FastAPI, Flask, etc.)
• Drive code quality, testing standards, and reusable architecture components
• Ensure solutions are performance optimised (latency, cost, reliability)
• Implement LLM guardrails (hallucination control, safety filters, policy enforcement)
• Define evaluation frameworks (response quality metrics, RAG benchmarking, human-in-the-loop validation)
• Drive end-to-end delivery ownership across multiple projects
• Mentor and guide junior engineers and project teams
• Conduct technical reviews, solution walkthroughs, and code reviews.

Lead AI Data Engineer

Cloud Engineer

• Manage data engineering projects, ensuring alignment with business objectives.
• Provide strategic guidance on data engineering best practices.
• Oversee a team of data engineers.
• Ensure continuous improvement of data processes.
• Design, build, and maintain efficient, reusable, and reliable architecture and code for data pipelines and data applications on AWS.
• Build robust data ingestion pipelines (from on-prem to AWS and within AWS) using AWS services such as Glue, Redshift, S3, Lambda, EMR/Spark, Kinesis, and SQS.
• Develop and manage ETL/ELT processes to collect, process, and store data from multiple sources, ensuring data quality, integrity, and security.
• Architect and implement end-to-end data solutions (ingestion, storage, integration, processing, access) on AWS, with a focus on data lakes and data warehouses.
• Participate in the architecture and system design discussions for high-scale data engineering projects.
• Independently perform hands-on development, unit testing, and participate in code reviews to ensure adherence to best practices.
• Implement serverless applications using AWS Lambda, API Gateway, Step Functions, and other AWS technologies.
• Migrate data from traditional relational databases, file systems, and APIs to AWS-based data lakes (S3), RDS, Aurora, and Redshift.
• Implement high-velocity streaming solutions using Amazon Kinesis, SQS, and Kafka (preferred).
• Architect and implement CI/CD strategies for enterprise data platforms.
• Collaborate with product, operations, QA, and cross-functional teams throughout the software development cycle.
• Stay abreast of new technology developments, implement POCs for new tools/technologies, and onboard them for real-world use cases.
• Identify and resolve performance issues and continuously optimize for cost, reliability, and scalability.

Senior AWS Data Engineer

Solutions Engineer

• Lead the design and development of advanced application solutions
• Define best practices for application development and deployment
• Oversee application project execution and resource management
• Ensure alignment of application solutions with business objectives
• Provide technical leadership on application initiatives.

Solution Architect

• Responsible for financial management – including revenue recognition, budgeting, forecasting, contract profit & loss management and customer invoicing
• Prepare variance analysis report and evaluate financial performance by comparing & analyzing actual results with budgets & forecast
• Prepare customer invoices and ensure efficient & accurate processing of invoices without any delay in timeline
• Understanding the contract clauses, deliverable and timelines related to client invoicing
• Liaison with operations and other functional areas to verify Invoice & forecast accuracy
• Process/Functional level data collation and reporting to Internal and External clients.
• Preparation, submission and presentation of various reports for the processes on agreed service level metrics with client.
• Regular maintenance of functional MIS and prepare performance analysis.
• Analyzing data and deriving meaningful results for the use of management in decision-making.
• Ensure accurate, timely and efficient reporting of Weekly, Monthly and Quarterly reports.
• Ensure compliance to client and organizational policies and procedures in respect of reporting.
• Maintain and develop the processes to ensure optimum automation of reports.
• Liaison effectively with leadership team, proving to be an effective and dependable support mechanism.
• Should show sufficient flexibility and urgency to handle pressure in a cross-cultural environment

Executive BSS

• Data modeling (conceptual, logical, physical)
• Designing end-to-end data architectures (ingestion → storage → processing → consumption)
• Defining standards for schemas, naming, versioning, and reuse
• Storage & Processing – relational databases, big data & analytics platforms, object storage
• Cloud Architecture – Azure/Microsoft Fabric fundamentals, cost optimization & scalability patterns, security & networking basics
• Translating business requirements into data structures
• Understanding business processes and operating models
• Explaining complex architectures to non-technical stakeholders
• Creating clear architecture diagrams and decision documents
• Facilitating design workshops and tradeoff discussion

Manager – Azure Data Architect

Software Engineer

• Design, build, and maintain ETL/ELT pipelines on Databricks using PySpark, Spark SQL, and Delta Lake.
• Develop and optimize data ingestion frameworks, data transformations, and end‑to‑end workflows for batch and streaming use cases.
• Implement Delta Lake‑based architectures, including versioning, schema evolution, and ACID‑compliant pipelines.
• Work with stakeholders to understand data requirements and translate them into scalable data engineering solutions.
• Manage and optimize Databricks clusters, jobs, and notebooks for performance and cost efficiency.
• Ensure data quality, reliability, and observability through validation frameworks and monitoring.
• Contribute to data modeling, metadata management, and best practices within the data platform.

Databricks Developer

• Design, develop, test, and deploy data integration processes (batch or real-time) using tools such as Microsoft SSIS, Azure Data Factory, Databricks, Matillion, Airflow, Sqoop, etc.
• Create functional & technical documentation – e.g. ETL architecture documentation, unit testing plans and results, data integration specifications, data testing plans, etc.
• Provide a consultative approach with business users, asking questions to understand the business need and deriving the data flow, conceptual, logical, and physical data models based on those needs.
• Perform data analysis to validate data models and to confirm ability to meet business needs.
• May serve as project or DI lead, overseeing multiple consultants from various competencies.
• Stays current with emerging and changing technologies to best recommend and implement beneficial technologies and approaches for Data Integration.
• Ensures proper execution/creation of methodology, training, templates, resource plans and engagement review processes.
• Coach team members to ensure understanding on projects and tasks, providing effective feedback (critical and positive) and promoting growth opportunities when appropriate.
• Coordinate and consult with the project manager, client business staff, client technical staff and project developers in data architecture best practices and anything else that is data related at the project or business unit levels.
• Architect, design, develop and set direction for enterprise self-service analytic solutions, business intelligence reports, visualizations and best practice standards.
• Toolsets include but not limited to: SQL Server Analysis and Reporting Services, Microsoft Power BI, Tableau and Qlik.
• Work with report team to identify, design and implement a reporting user experience that is consistent and intuitive across environments, across report methods, defines security and meets usability and scalability best practices

Lead Assistant Manager – Azure Data Engineer

Recruitment

• Source and screen candidates
• Manage the interview process
• Ensure a positive candidate experience
• Collaborate with hiring managers
• Handle job postings
• Maintain accurate records in the applicant tracking system
• Support onboarding and compliance
• Participate in campus recruitment efforts
• Stay informed on industry trends and suggest improvements

Senior Associate – Talent Acquisition Specialist

Account Executive

• Processing NON PO/PO Invoices
• Enter time-sensitive Utility invoices and research any past due amounts to ensure for current accounts
• Ensure SLA target are achieved
• Month-end responsibilities include ensuring that all invoices are processed by month-end
• Ability to comprehend complex information quickly & respond with clear solutions

EXL

Senior Executive

Lead Security Engineer – DevSecOps

Senior Executive – P2P Invoice Processing

Principal Architect, AI Data Engineer

Architect, AI Data Engineer

Architect, AI Data Engineer

Lead AI Data Engineer

Senior AWS Data Engineer

Solution Architect

Executive BSS

Manager – Azure Data Architect

Databricks Developer

Lead Assistant Manager – Azure Data Engineer

Senior Associate – Talent Acquisition Specialist

Senior Executive – Accounts Payable