Job Description: Solutions Architect (AI & Data)Role Metadata
- Job Title: Solutions Architect
- Function: Engineering – AI & Data
- Business Unit: REIL (Reliance Enterprise Intelligence Ltd)
- Location: Mumbai, India
- Experience: 10–14 Years
- Employment Type: Full-Time
About REIL
Reliance Enterprise Intelligence Ltd (REIL) is a premier joint venture between Reliance Industries and Meta. By combining Reliance’s unparalleled scale and deep enterprise domain expertise with Meta’s world-class AI capabilities and cutting-edge technology infrastructure, REIL is uniquely positioned to redefine enterprise intelligence.
About the Programme
We are building a next-generation, enterprise-grade AI platform focused on financial compliance and intelligence. This platform is designed to handle massive data scales, deliver high-precision compliance logic, and eventually expand into a commercially licensed product for external global organizations.
Role Overview
We are seeking a seasoned, hands-on Solutions Architect to own the technical vision and architectural design of our AI compliance platform from the ground up.
Note: This is not a hands-off, theoretical architecture role. You will spend your initial weeks deeply embedded with compliance operations to understand complex financial logic before proposing any design. You will serve as the absolute technical authority for the engineering squad, making foundational architectural choices that ensure production reliability, scalability, and zero-fault tolerance in a regulatory compliance environment.Key Responsibilities1. Problem Definition & Discovery
- Deep-Dive Alignment: Partner directly with compliance consultants, operations, assurance, and IT teams to map out end-to-end compliance workflows, data flows, and legacy system constraints.
- Data Landscape Mapping: Assess the current data platform, pinpoint extraction requirements from various source systems, and identify critical technical gaps.
- Risk Mitigation: Surface technical constraints, integration challenges, and delivery risks early to design proactive architectural workarounds.
2. End-to-End AI System Architecture
- Blueprint Creation: Design the comprehensive AI system architecture, spanning the data ingestion layer, ML model pipelines, LLM/RAG frameworks, real-time API layers, and user applications.
- Technical Documentation: Produce and maintain the foundational technical architecture documents (data flow diagrams, component breakdowns, API contracts, and technology stack choices) that the squad builds against.
- Pragmatic Technology Selection: Define the right approach for specific use cases—discerning when to deploy traditional ML models, when to leverage LLMs, and where rule-based logic is most efficient.
3. Technical Governance & Engineering Leadership
- Technical Authority: Act as the ultimate technical anchor for the engineering squad, ensuring all stream-level decisions align with the macro blueprint.
- Architecture Reviews: Conduct regular design and code reviews with engineering streams as the build progresses.
- Velocity Management: Resolve daily technical blockers to maintain high squad velocity toward an aggressive 8-week pilot delivery.
- Scalability & Tech Debt: Balance rapid delivery needs with long-term platform scalability, ensuring the system can scale commercially to external organizations without requiring a full rebuild.
4. Data & Integration Architecture
- Ingestion Pipelines: Architect robust data ingestion mechanisms across diverse sources including ERPs, government portals, supplier networks, and banking feeds.
- Real-Time Integration: Define real-time data feeds where low latency is critical to operational workflows.
- Fallback Mechanisms: Design integration layers that funnel AI outputs back into operational systems, establishing strict fallback guardrails when model confidence scores fall below compliance thresholds.
Qualifications & SkillsRequired Education & Experience
- Education: B.E. / B.Tech / M.Tech in Computer Science, Information Technology, or a related field from a reputed institution.
- Experience: 10+ years of software engineering experience, including 4–5 years as a Solutions Architect or Principal Engineer.
- Proven Track Record: Demonstrated success designing and deploying production-grade, enterprise-scale AI/ML systems (not just proof-of-concepts).
- Enterprise Savvy: Proven experience navigating complex enterprise environments with multiple legacy systems, source integrations, and real-time processing constraints.
Core Technical Skills
- Programming: Expert-level Python; working knowledge of at least one other language (Java, Go, or Node.js).
- AI/ML: Comprehensive ML system design experience (training, evaluation, deployment, monitoring, classification, anomaly detection, and clustering).
- LLM & RAG: Production-grade Retrieval-Augmented Generation (RAG) architectures, vector databases, prompt engineering for structured outputs, and LLM evaluation frameworks.
- Data Architecture: Deep understanding of data lakes, real-time vs. batch processing pipelines, and data quality frameworks. Strong preference for Databricks and Delta Lake.
- Integration: Modern REST API design, event-driven architectures, and enterprise system integrations (ERP integration experience is highly preferred).
- MLOps & Observability: Hands-on familiarity with MLflow, model registries, inference latency optimization, distributed tracing, and production alerting frameworks.
Preferred (Bonus) Qualifications
- Direct domain experience in fintech, tax technology, compliance, or legal tech.
- Familiarity with SAP data models and extraction patterns.
- Prior exposure to Indian government API ecosystems (such as GSTN).
- Experience architecting Explainable AI (XAI) outputs for regulatory or audit purposes.
- Experience building software platforms intended for external commercial licensing.
- Active contributions to the technical community (published architectures, whitepapers, open-source contributions, or conference talks).
Pay: ₹903,764.62 - ₹2,476,080.00 per year
Benefits:
- Health insurance
- Paid sick time
- Provident Fund
Work Location: In person
