About the Role

We are seeking an AI Platform Engineer to architect next-generation CFO copilots and Agentic AI workflows for financial planning and analysis (FP&A). In this role, you will design autonomous AI systems that interpret business queries, generate SQL, trigger actions, and learn continuously through feedback loops. You’ll work with LLMs, LangChain, data engineering, and middleware to deliver enterprise-grade AI copilots for finance, transforming processes such as budgeting, forecasting, reconciliation, and variance reporting.

Roles & Responsibilities

1. Agentic AI Development

Build and orchestrate AI Agents for workflows: budgeting, forecasting, reconciliation, alerts, and variance analysis.
Design multi-step prompt flows, agent memory, and tool integration using LangChain, OpenRouter.

2. LLM Applications & Context Engineering

Integrate leading models (GPT-4, Claude, Gemini, LLaMA, Mistral) for finance-specific tasks.
Implement RAG pipelines to query structured/validated datasets (Medallion architecture: Bronze–Silver–Gold).

3. Conversational Interfaces

Build AI chat assistants for CFO, sales, and collections teams.
Implement backend integration, streaming responses, conversational memory, and prompt logging.

4. Data Engineering for AI

Develop ETL/ELT pipelines to sync data from CRMs, ERPs (SAP/Oracle), accounting tools (Xero, Zoho), and SQL warehouses.
Build AI APIs and design systems using Medallion Architecture.

5. Auto-Digest & Exception Reporting Engines

Automate insight digests via bots (email/WhatsApp).
Apply ML to detect anomalies, spikes, and drop-offs in KPIs.

6. Cloud Deployment & DevOps

Deploy AI systems using Azure AI, AWS Bedrock, GCP Vertex, Supabase.
Containerize services with CI/CD pipelines for production-ready releases.

7. Security & Compliance

Enforce guardrails, moderation APIs, and PII masking.
Ensure compliance with GDPR, SOC2, ISO 27001 for enterprise-grade deployments.

8. Agentic AI in Automation & EPM

Develop AI agents for approval workflows, reconciliations, and alerts.
Embed AI copilots into budgeting & EPM modules for consolidation, exception handling, and planning.
Implement multi-agent orchestration for financial insights and decision automation.

9. Unstructured Data Integration

Ingest and process PDFs, emails, chats, audit notes, and scanned docs.
Build OCR pipelines and vector-based semantic search on non-tabular inputs.

10. Predictive & Prescriptive Analytics

Create ML models for demand forecasting, churn prediction, collections, and cash flow.
Use deep learning (LSTM, Transformers) for real-time predictive insights.

11. Optimization & Efficiency Modules

Design optimization models (linear/integer programming) for budget allocation and cost control.
Automate reporting, audit, and reconciliation tasks for efficiency gains.

12. Continual Learning & Feedback Loop

Implement feedback-driven learning systems from user ratings (thumbs up/down).
Maintain prompt knowledge bases and apply human-in-the-loop reviews for continual improvement.

Qualifications Required

Bachelor’s or Master’s degree in Computer Science, Data Engineering, or related field.
Strong programming skills in Python, SQL/NoSQL.
Hands-on experience with LLMs, LangChain, embeddings, and vector databases.
Proficiency in ML/DL frameworks: TensorFlow, PyTorch, Scikit-learn, OpenCV, Keras.
Solid understanding of financial data workflows, FP&A, and EPM modules (preferred).
Experience with cloud platforms (Azure, AWS, GCP) and containerization (Docker, Kubernetes).
Familiarity with compliance frameworks (GDPR, SOC2, ISO 27001).
Strong problem-solving, system design, and communication skills.

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