Role Overview

OFI Services is seeking a Technical Consulting Manager to lead the architecture and delivery of enterprise-grade solutions across cloud, data, AI and automation platforms. You will define how solutions are designed and built, choose the right platforms and services for each concern, and ensure that teams deliver them to a high engineering standard. You will own technical direction and delivery quality, guide a team of engineers and consultants, and act as the escalation point for complex architecture, integration and performance challenges.

This is a design-and-lead role, not an individual-contributor build role. The ideal candidate has a track record of architecting large solutions that teams then build and operate, and remains technical enough to challenge designs, review code and make sound platform choices. You will also grow into broader team and client leadership.

Key Responsibilities

Solution Architecture and Design

- Define the end-to-end technical architecture for enterprise solutions, from requirement gathering and discovery through design, build, testing, deployment, hypercare and production support.
- Select and justify platforms and services (build, buy or configure) against client needs, cost, security and scalability, using standard or custom platforms as appropriate.
- Review and approve solution designs, data models and code produced by the team; set engineering standards, architecture decision records and peer-review practices.
- Produce reference architectures, patterns and reusable accelerators that can be applied across engagements.

Cloud, Platform and DevOps Engineering

- Architect solutions on GCP, Microsoft Azure and the wider Microsoft ecosystem (for example Microsoft Fabric, Power Platform, Entra ID and Microsoft 365), selecting best-in-class services for each need.
- Establish Infrastructure as Code, CI/CD and DevOps standards (for example Terraform or Bicep with GitHub Actions, Azure DevOps or Cloud Build) with automated testing, setting promotion and release governance.
- Design identity and access management, secrets management and security controls, including role-based access, single sign-on, least-privilege and audit trails.
- Define observability, monitoring, alerting and incident management practices across applications, data pipelines and AI workloads (for example OpenTelemetry, Azure Monitor and Google Cloud Operations).
- Guide non-functional design: performance, resilience, disaster recovery, cost management (FinOps) and compliance.

Data Engineering and Knowledge Platforms

- Oversee the design and optimisation of data platforms and pipelines: ingestion, ETL/ELT, orchestration,



data modelling, data quality and lineage.
- Lead integration with enterprise applications such as SAP ECC/S/4HANA, Oracle, Salesforce and ServiceNow, ensuring data quality, scalability and performance.
- Design knowledge graph solutions (for example Neo4j and other graph or semantic technologies) and ontologies that connect enterprise data for analytics, search and AI use cases.
- Set standards for data governance, security, access control and data validation.

AI, Automation and Enterprise Platforms

- Design AI solutions that use large language models appropriately, including hosted models such as Claude and self-hosted or open-weight models run through tools such as Ollama, with attention to retrieval, agents, guardrails, evaluation, data privacy and cost.
- Architect extensions and integrations on SAP Business Technology Platform (BTP), including the use of SAP Joule and AI capabilities within SAP landscapes.
- Lead intelligent automation design using UiPath and related tools such as Power Automate, combining RPA, APIs and AI in governed, scalable operating models.
- Oversee process intelligence solutions, including Celonis (PQL, object-centric process mining, Action Flows and AI features), where these form part of the client solution.

Delivery and Team Leadership

- Own delivery of engagements end to end: scoping, estimation, planning, solution delivery, hypercare and handover to production support.
- Lead, coach and develop a team of consultants and engineers; run staffing, performance reviews and career development.
- Mentor the team, run technical training and support certification paths across cloud, data and platform skills.
- Manage engagement financials, including budgets, utilisation, forecasting and margin.
- Build reusable assets, templates and best practices, and set delivery quality standards for the team.

Client and Practice Leadership

- Act as the senior technical contact for business sponsors, process owners and IT leadership; manage expectations, risks, scope and escalations.
- Support pre-sales and solutioning: discovery workshops, architecture proposals, demos, proofs of value, sizing and statements of work.
- Track the technology landscape and vendor roadmaps (cloud, SAP, AI and automation)



and share new capabilities with the team and clients.
- Represent OFI in client steering committees and internal practice forums.

Required Skills and Experience

Architecture and Delivery

- Proven experience designing and delivering enterprise-scale solutions, where the team builds to your architecture and you own design quality and delivery outcomes.
- Ability to evaluate standard versus custom platforms and make clear, defensible technology choices.
- Ability to estimate effort, manage technical risk and lead delivery across multiple concurrent workstreams.

Cloud and Engineering Practices

- Strong working knowledge of GCP and/or Azure, and of Microsoft platforms and tools.
- Hands-on grounding in Infrastructure as Code, CI/CD, DevOps, identity and access management, and observability, with the judgement to choose best-in-class tooling for each.

Platforms, AI and Automation

- Experience with SAP BTP and SAP Joule, UiPath, and LLM platforms such as Claude and Ollama.
- Experience with knowledge graphs (Neo4j and similar technologies), including data modelling and query languages such as Cypher.
- Working knowledge of Celonis or other process mining platforms is an advantage (see Good to Have).

Data Engineering

- Good understanding of data engineering tools and concepts: ETL/ELT, orchestration, data warehouses and lakehouses, streaming and batch processing, data modelling, governance and quality.
- Working knowledge of SQL and Python (Spark is a plus), sufficient to review designs and code and guide the team.
- Experience integrating enterprise applications such as SAP, Oracle, Salesforce and ServiceNow.

Required Qualifications

- 10+ years of experience in software, data or cloud engineering, solution architecture or technology consulting, with at least 5 years architecting enterprise solutions and at least 3 years leading teams or workstreams.
- Proven record of delivering enterprise programmes across at least two industries or business domains (for example finance, supply chain, procurement or manufacturing).
- Excellent communication, stakeholder management and executive presentation skills.
- Strong problem-solving ability and comfort working with ambiguity.
- Bachelor’s degree in Engineering, Computer Science or a related field (Master’s or MBA preferred).

Good to Have

- Hands-on experience with Celonis, including PQL and object-centric process mining.
- Exposure to AWS in addition to GCP and Azure.
- Experience with agentic AI patterns, the Model Context Protocol (MCP) and AI governance frameworks.
- Experience with Task Mining or other process intelligence tools.

📌 Consulting Manager (Bengaluru)
🏢 Artefact
📍 Bengaluru