Senior Solution Architect – Functional Architect

Jobtailor

Dadri

On-site

INR 6,000,000 - 12,000,000

Full time

14 days+

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Job summary

Jobtailor seeks a senior AI product leader to own the end-to-end vision and multi-year roadmap for AI-powered Accounts Payable solutions. You will define architectures for Generative AI and Agentic AI within AP workflows and drive deployment across AWS, Azure, and GCP.

You will mentor ML engineers and data scientists, manage vendor ecosystems, and translate business goals into scalable MLOps pipelines and secure cloud AI pipelines.

Qualifications

14–16 years of total experience in product engineering or leadership roles.
8+ years of AI/ML product engineering experience with hands-on Generative AI and LLM
8+ years of Finance tech experience with deep AP/P2P domain ownership
Hands-on experience with PyTorch and TensorFlow demonstrated in production
Strong ability to translate business requirements into scalable AI architectures

Responsibilities

Own the end-to-end product vision and multi-year roadmap for AI-powered AP solutions.
Define architecture and feature sets for Generative AI within AP workflows.
Lead client engagements and present technical roadmaps to C-suite audiences.

Skills

AI product leadership

MLOps

Python

PyTorch

Generative AI

NLP

Cloud architectures

Stakeholder management

Education

B.Tech/M.Tech in CS/DS

M.Tech in AI/DS

Tools

MLflow

Pinecone

Weaviate

Pgvector

AWS

Azure

GCP

Job description

Own the end-to-end product vision and multi-year roadmap for AI-powered Accounts Payable solutions, including invoice processing, three-way matching, supplier onboarding, exception management, and payment orchestration
Define product architecture and feature sets for Generative AI and Agentic AI capabilities within AP workflows
Participate in architectural discussions and design scalable AP AI solutions for AWS, Azure, and GCP deployment
Drive build-vs-buy-vs-partner decisions for AI frameworks and vendor ecosystems
Design Generative AI solutions using GPT-4o, Claude, and Llama 3 for invoice extraction, PO matching, and vendor communication
Architect autonomous agentic AI workflows for exception handling, approval orchestration, and supplier query resolution
Translate AP business requirements into AI architectures, orchestration frameworks, and scalable MLOps/MLflow deployment pipelines
Design NLP and Intelligent Document Processing capabilities for invoices, POs, GRNs, contracts, and remittance advices
Ensure solutions meet SOX, GDPR, security, scalability, and enterprise data-governance standards
Guide data scientists, ML engineers, and software engineers building, fine-tuning, and deploying LLM and multimodal AI models
Architect secure cloud AI pipelines and drive adoption of deep learning and LLM orchestration stacks
Monitor Generative AI, agentic systems, NLP, and ML engineering advances and translate them into product features
Drive code quality, MLOps, model versioning, and production monitoring
Engage client CTOs, CPOs, and finance technology leaders to understand AP needs and co-create transformation roadmaps
Lead client solutioning, proof-of-concepts, scope definition, and presentations for technical and business audiences
Create whitepapers, workshops, demo environments, and proof-of-concept accelerators
Represent EXL in industry forums, analyst briefings, and RFI/RFP responses as the Finance AI product SME
Build relationships with senior client stakeholders and enable internal AI advocacy
Maintain a prioritized product backlog with PRDs, user stories, and acceptance criteria
Establish product KPIs including STP rates, invoice auto-match accuracy, exception reduction, and cycle-time improvements
Share best practices across EXL AI product and solutions architect communities
Mentor product managers, solution architects, ML engineers, and finance SMEs

Requirements

B.Tech or M.Tech in Computer Science, Software Engineering, Data Science, or a related technical discipline
14–16 years of total experience
At least 6–8 years of AI/ML product engineering experience
8+ years of Finance technology experience with deep Accounts Payable/P2P domain ownership
8+ years of hands‑on Generative AI and Large Language Model experience, including LLM fine‑tuning, prompt engineering, and orchestration frameworks
Hands‑on experience with PyTorch and TensorFlow demonstrated through production deployments or public repositories
Understanding of deep neural‑network optimization, regularization, hyperparameter tuning, and finance‑specific model fine‑tuning
Strong Agentic AI experience with autonomous agents, AutoGen, CrewAI, and LangGraph; familiarity with NVIDIA AI Blueprints and Google AI Agents
ML Engineering and MLOps experience, including MLflow, model versioning, drift monitoring, and retraining pipelines
Proven ability to deliver complex enterprise AI products from ideation through production and drive go‑to‑market
Strong Python software‑engineering skills, including AI APIs, microservices, and cloud‑native architectures
Deep Accounts Payable knowledge, including P2P lifecycle, ERP integrations, invoice automation, and supplier management
NLP and IDP experience, including OCR, entity extraction, document classification, and structured data extraction
Understanding of graph and vector databases, including Pinecone, Weaviate, and pgvector
Experience with AWS Bedrock/SageMaker, Azure OpenAI, and GCP Vertex AI for inference and fine‑tuning
Ability to present AI concepts and product roadmaps to C‑suite audiences
Experience with RFI/RFP responses, thought leadership, and AI/Finance technology business development
Ability to manage data scientists, ML engineers, and product managers while remaining technically hands‑on
Working knowledge of classification, regression, anomaly detection, and time‑series analysis applied to finance data

Core Competencies

Demonstrates expertise in AI-powered Accounts Payable solutions, including Generative AI and Large Language Model development, while ensuring compliance with financial regulations and enterprise data governance. Proven ability to lead cross‑functional teams in delivering complex AI products from ideation to production.

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