We are hiring an Agentic Solutions Architect to design production-grade agentic solutions on our internal platform across multiple delivery squads. This role connects business needs, product intent, and engineering execution: you will understand the problem to solve, shape viable options, make and communicate tradeoffs, be hands on keyboard coding, manage a team of engineers, and guide squads toward secure, observable, reusable, and supportable outcomes.
You will architect across several squads rather than serving as the architect for a single use case. You will partner with Product, Program, Tech Leads, engineers, security, and business stakeholders to ensure solution architectures align with the platform standards and broader engineering strategy.
What You'll Do
Partner with team leadership and business stakeholders to understand goals, workflows, users, constraints, and success measures.
Help determine whether an agentic solution is appropriate, or whether a deterministic workflow, existing capability, or no-AI solution is better.
Be able to challenge the status quo and look for simplicity, scalability, and staged solutions that deliver incremental value when needed.
Translate business needs into technical requirements, scope boundaries, delivery roadmaps, architectural options, measurable outcomes, and implementation plans.
Explain technical implications and communicate tradeoffs across scope, cost, quality, latency, security, risk, and delivery speed.
Own solution architecture for a portfolio of use cases and agentic applications delivered by several squads within a larger delivery organization.
Map end-to-end workflows, trigger events, human approvals, system interactions, failure paths, and operational handoffs.
Define agent package structure, task graphs, orchestration patterns, and the division of responsibility between agents, deterministic code, tools, and platform services. Identify required systems, data sources, outputs, APIs, integrations, tools, and MCP capabilities.
Work with partners to ensure dependencies are accounted for and managed across the portfolio of solutions in the role’s purview.
Produce architecture diagrams, decision records, implementation guidance, acceptance criteria, and nonfunctional requirements.
Manage cross-squad dependencies, technical debt, duplicate capabilities, and opportunities for reusable patterns, templates, connectors, and reference implementations.
Collaborate with delivery teams to translate architecture into work packages, estimates, quality criteria, and delivery plans.
Be hands on keyboard to guide and work with the teams and understand solutions to a granular level.
Apply architecture standards, approval controls, guardrails, and governance requirements throughout delivery.
Work with leadership to maintain solution architecture across teams for technical direction, engineering standards, capacity, and risk posture.
Support developer onboarding and architecture education across squads.
Coordinate decisions and dependencies across product, engineering, security, data, integrations, and business teams.
Communicate architecture status, risks, dependencies, and tradeoffs to technical and executive audiences.
Directly manage engineers executing across multiple small, focused product squads.
What You'll Bring
Required experience
AWS and cloud-hosted foundation models or agent platforms, such as Amazon Bedrock or AgentCore, or equivalent technologies.
Python, TypeScript/JavaScript, REST or GraphQL APIs, event-driven systems, serverless or containerized workloads, and infrastructure as code.
Significant experience in software architecture, solutions architecture, technical leadership, or a similar role designing and delivering enterprise systems.
Experience architecting and shipping production AI, generative AI, agentic, conversational, or intelligent-automation solutions.
Strong understanding of agentic patterns, including orchestration, tool use, RAG, model selection, prompt and policy controls, human-in-the-loop approval, state and memory, evaluation, and fallback behavior.
Experience integrating enterprise systems through APIs, events, connectors, workflow engines, or MCP-style tool patterns.
Strong understanding of identity, authorization, data access, privacy, auditability, and secure-by-default design.
Demonstrated ability to influence multiple teams or squads without relying solely on formal authority.
Excellent written and verbal communication, including the ability to explain complex architecture and tradeoffs to business stakeholders and executives.
Leading architecture reviews involving security, compliance, privacy, or production risk.
Relevant cloud, security, AI, or architecture certifications. Certifications are helpful but are not a substitute for demonstrated production experience.
Experience coordinating and managing the work of engineers against a timeline.
What Success Looks Like
Multiple squads can move independently while following coherent architecture patterns and shared platform standards.
Business stakeholders understand solution options, key tradeoffs, and expected outcomes before significant implementation investment.
Each solution has clear boundaries, documented decisions, nonfunctional requirements, security controls, operational ownership, and a credible path to production.
Reusable capabilities are adopted across squads instead of repeatedly rebuilt as bespoke solutions where possible.
Risks, dependencies, exceptions, and technical debt are visible early and actively managed.
Solutions deliver measurable business value while meeting expectations for quality, safety, reliability, observability, and cost.
Squad leaders share a clear view of how use-case architecture supports platform engineering goals.
Ovii Interpretation
The Agentic Solutions Architect shapes and guides production AI and agentic solutions across multiple delivery squads. The role connects business goals with product and engineering plans, defines secure and reusable architectures, and combines hands-on technical guidance with direct management of engineers.
AWSAmazon Bedrock or AgentCoreor equivalent agent platformsPythonTypeScript or JavaScriptREST or GraphQL APIsEvent-driven systemsServerless or containerized workloadsInfrastructure as codeAgent orchestration
What you will likely work on
Assess business workflows and decide whether agentic AI, deterministic automation, an existing capability, or no AI is the right fit.
Turn business goals into architecture options, technical requirements, delivery plans, scope boundaries, and measurable outcomes.
Design agent workflows, task graphs, orchestration, integrations, data flows, approvals, failure handling, and operational handoffs.
Guide production-ready architectures with security, reliability, observability, supportability, and platform standards in view.
Coordinate architecture, dependencies, risks, technical debt, and reusable patterns across several squads.
Work hands-on with delivery teams to shape implementation, work packages, estimates, acceptance criteria, and quality expectations.
Communicate architecture decisions and tradeoffs to business, technical, and executive stakeholders.
Manage engineers across multiple small product squads and support developer onboarding and architecture education.
Good fit signals
Brings significant experience designing and delivering enterprise systems in a software or solutions architecture, or technical leadership role.
Has architected and shipped production AI, generative AI, agentic, conversational, or intelligent-automation solutions.
Can influence multiple teams while clearly explaining technical choices and tradeoffs to business stakeholders and executives.
Understands secure enterprise integration, including identity, authorization, privacy, data access, and auditability.
Experience establishing reusable architecture practices or coordinating engineers to timelines is helpful; relevant certifications are also helpful, not a substitute for production experience.
Meet Ahead
Acceldata develops enterprise software for data observability, data management and AI operations. Its xLake platform combines data quality checks, pipeline monitoring, lineage, governance and compute management across cloud, on-premises and hybrid environments. Products include Acceldata Data Observability Cloud, Agentic Data Management, AI Observability and an Open Data Platform for Hadoop modernization. It also offers xFactory, introduced in early access for building AI agents and applications on governed enterprise data. Its tools help data teams detect unreliable data, investigate pipeline failures, control infrastructure costs and support analytics and AI workloads. Customers include Dun & Bradstreet, PubMatic, PhonePe and HCSC.
Founded
2018
Company size
201-500 employees
Company stage
Not known
Headquarters
Campbell, USA
Why work here
Acceldata offers engineering work on distributed systems, data reliability and AI agents using technologies such as Java, Python, Kubernetes and LangChain. It has raised over US$100 million and serves enterprises including Dun & Bradstreet, PubMatic and PhonePe, providing exposure to large-scale data problems. Published Bengaluru engineering roles list ESOPs, medical and life insurance, paid maternity and parental leave, mentorship and learning support. Those roles are advertised as on-site.
RCRohit ChoudharyFounder and Chief Executive OfficerView bioHide bio
Co-founded Acceldata in 2018 and serves as CEO. Previously Director of Engineering at Hortonworks, where he led development of Dataplane Services, Apache Ambari and Apache Zeppelin. His experience building large-scale data systems at Hortonworks and Zalando informed Acceldata's focus on data reliability and observability.
ARAshwin RajeevaCo-Founder and Chief Technology OfficerView bioHide bio
Co-founded Acceldata in 2018 and serves as CTO, leading technology vision, architecture and engineering. Previously held engineering and architecture roles at Hortonworks, Zalando, Thoughtworks and [24]7.ai. His expertise spans distributed systems, big-data infrastructure and large-scale analytics platforms.
RKRaghu KandikondaCo-Founder and Vice President of EngineeringView bioHide bio
Co-founder and Vice President of Engineering, leading engineering for data observability and Agentic Data Management. Previously worked at Hortonworks and contributed to the Apache Software Foundation ecosystem. His expertise includes distributed systems and AI-driven enterprise data platforms.
Co-founded Acceldata in 2018 after working at Hortonworks and serves as Senior Architect. He was part of the four-person founding team that established the company's approach to enterprise data reliability and observability, bringing experience in complex data systems.
MMMike McQuaidChief Revenue OfficerView bioHide bio
Leads Acceldata's sales strategy. Brings more than 20 years of enterprise technology experience, including roles at Hitachi Vantara, BusinessObjects and Birst, and experience managing large field-sales organizations.
MKMahesh KumarChief Marketing OfficerView bioHide bio
Leads global marketing strategy. Brings more than 30 years of technology marketing experience, including work at GitLab and Propelo, which was acquired by Harness, and experience developing software market categories.
Leads product strategy. Brings more than 30 years of experience across cloud platforms, SaaS applications and infrastructure, including roles at ActivTrak and Reltio, with expertise relevant to enterprise data management and analytics.
SWSamuel WolffChief Financial OfficerView bioHide bio
Leads Acceldata's finance function. Previously served as CFO at Singular and has experience at Yahoo, BlueKai and Birst. His background includes scaling technology businesses, capital allocation and evaluating the economics of enterprise AI.
AGAshok GunasekaranSenior Vice President, Customer SuccessView bioHide bio
Leads customer success at Acceldata. His experience includes building global technical customer success and support teams of more than 300 people, with expertise in digital customer experience and scaling customer-facing operations.
Acceldata releases ADOC 26.10.0 with expanded lakehouse monitoring
Acceldata·
The release adds Apache Kyuubi integration for monitoring private-cloud lakehouses, improved pipeline run investigation and a dashboard for tracking data quality across published data products.
Acceldata launches xFactory for governed enterprise AI applications
Acceldata·
Introduced xFactory in early access for existing xLake customers. The platform builds, tests and deploys AI agents, applications and analytics from business requests using governed data across hybrid enterprise environments.
Acceldata adds AI Observability to its xLake Data Platform
Acceldata·
The new capability traces prompts, model calls, tools and retrieval steps, connecting AI application behavior with data quality, lineage and pipeline monitoring across cloud and on-premises systems.