Solution Architect – AI Infrastructure & Private Cloud

Job Description: Lead - Cloud Engineering (AWS / Azure)

Role Title: Lead - Cloud Engineering

Experience Level: 10+ Years

Domain Focus: Healthcare AI & Cloud Infrastructure

Location: Remote

Job Overview

We are seeking an experienced Lead - Cloud Engineering with over 10 years of IT experience to lead our cloud strategy, architecture, and infrastructure teams. In this role, you will oversee end-to-end cloud deployment, multi-cloud migration, and scalable architecture designed to support cutting-edge Generative AI applications in the healthcare technology domain.

The ideal candidate brings deep technical expertise in both AWS and Azure, strong hands-on capability in cloud infrastructure, and proven leadership experience driving security, compliance, and team growth.

Key Responsibilities

Cloud Architecture & Migration

• Lead the architecture, design, and execution of cloud migrations, deployments, and modernizations across AWS and Azure environments.
• Drive Infrastructure as Code (IaC) standards using Terraform, CloudFormation, or Bicep to ensure scalable, automated infrastructure provisioning.
• Build high-availability, low-latency architectures optimized for data-intensive Generative AI and Machine Learning workloads.

Security & Healthcare Compliance

• Enforce healthcare security standards including HIPAA, HITRUST, SOC 2, and data governance best practices across all cloud assets.
• Implement Zero-Trust security, Identity Access Management (IAM), data encryption key management, and continuous vulnerability monitoring.

Leadership & Team Management

• Manage, mentor, and scale a high-performing team of DevOps, Cloud, and SRE Engineers.
• Drive Agile workflows, sprint planning, incident response frameworks, and SLA compliance.
• Collaborate closely with Data Engineering, AI/ML, and Software Product teams to align infrastructure with business roadmaps.

Operations & FinOps

• Establish cloud cost optimization strategies (FinOps) to manage computing costs associated with AI models and large-scale data processing.
• Manage monitoring, alerting, and telemetry frameworks (e.g., Prometheus, Datadog, CloudWatch) to ensure 99.99% uptime.

Key Requirements

• Experience: 10+ years of overall IT experience with at least 5+ years in a cloud leadership or lead architect role.
• Cloud Platforms: Advanced hands-on expertise with both AWS (e.g., EC2, S3, EKS, Bedrock, SageMaker) and Azure (e.g., AKS, Azure OpenAI, Blob, Virtual Machines).
• DevOps & IaC: Strong background in Terraform, Docker, Kubernetes, CI/CD pipelines (GitHub Actions, GitLab CI, or Jenkins).
• Domain Knowledge: Prior experience building or managing cloud environments within Healthcare, Life Sciences, or HealthTech is strongly preferred.
• AI/ML Familiarity: Experience supporting cloud infrastructure for machine learning pipelines, LLM deployments, or GPU compute management.
• Certifications (Preferred): AWS Certified Solutions Architect – Professional, Azure Solutions Architect Expert, or Certified Kubernetes Administrator (CKA).

Amura’s Vision 

We believe that the most under-appreciated route to releasing untapped human potential is to build a healthier body, and through which a better brain. This allows us to do more of everything that is important to each one of us.

Billions of healthier brains, sitting in healthier bodies, can take up more complex problems that defy solutions today, including many existential threats, and solve them in just a few decades.

Billions of healthier brains will make the world richer beyond what we can imagine today. The surplus wealth, combined with better human capabilities, will lead us to a new renaissance, giving us a richer and more beautiful culture.

These healthier brains will be equipped with deeper intellect, be less acrimonious, more magnanimous, and have a kinder outlook on the world, resulting in a world that is better than any previous time.

We find this vision of the future exhilarating. Our hopes and dreams are to create this future as quickly as possible and ensure that it is widely distributed and optimized to maximize all forms of human excellence. 

Role Overview 

We are looking for a highly skilled Senior DevOps Engineer (AI-Native Infrastructure & Platform Engineering) with deep expertise in AWS cloud infrastructure, automation, AI infrastructure operations, and modern DevOps/SRE practices.

This role goes beyond traditional DevOps and requires a seasoned specialist capable of building and operating AI-ready infrastructure platforms that support high-throughput APIs, LLM/AI workloads, GPU-based compute, data-intensive systems, real-time inference pipelines, and scalable ML platforms.

You will be responsible for architecting, automating, securing, and optimizing highly scalable and cost-efficient cloud environments that enable high-velocity engineering and AI teams. This is an ideal position for someone who combines technical ownership, an automation-first mindset, and a passion for developer productivity and platform reliability. 

Key Responsibilities 

Cloud Infrastructure & Platform Engineering (AWS) 

• Architect, deploy, and manage highly scalable and secure infrastructure on AWS. Design cloud platforms supporting AI/ML workloads, data pipelines, real-time APIs, and high-concurrency backend systems.
• Hands-on expertise with key AWS services including EC2, ECS/EKS, Lambda, RDS, DynamoDB, S3, VPC, CloudFront, IAM, CloudWatch, and GPU-enabled instances.
• Build and maintain Infrastructure-as-Code (IaC) using Terraform, CloudFormation, or AWS CDK.
• Design multi-AZ and multi-region architectures for high availability and disaster recovery (HA/DR).
• Build reusable platform templates and shared infrastructure modules. 

AI/ML Infrastructure & MLOps 

• Build and maintain infrastructure for LLM applications, AI inference workloads, model serving platforms, vector databases, and feature stores.
• Support GPU-based workloads and optimize compute/storage usage.
• Enable scalable deployment patterns for AI applications using Kubernetes/EKS. Collaborate with Data Science and ML Engineering teams on model deployment, training/tuning of models, CI/CD for ML systems, experiment environments, and reproducibility.
• Support orchestration and deployment of AI workflows and inference services while implementing observability and reliability for AI pipelines. 

CI/CD, Automation & Developer Productivity 

• Build and maintain CI/CD pipelines using GitHub Actions, GitLab CI, Jenkins, or AWS CodePipeline.
• Automate deployments, environment provisioning, and release workflows.
• Build self-service developer platforms, preview environments, and reusable deployment workflows to improve developer productivity.
• Implement automated patching, scaling, backups, cleanup workflows, and drift detection. 

Containers, Kubernetes & Platform Reliability

• Manage Docker-based environments, containerized applications, and optimize workloads using Kubernetes (EKS) or ECS/Fargate.
• Manage autoscaling, cluster health, node pools, ingress, service mesh, and workload isolation.
• Optimize infrastructure for performance, resilience, and cost-efficiency.
• Implement progressive deployment strategies including blue/green, canary, and rolling deployments. 

Observability, Incident Response & SRE Practices

• Implement observability stacks using CloudWatch, Prometheus, Grafana, ELK, Datadog, OpenTelemetry, or New Relic.
• Build actionable dashboards and intelligent alerting systems while defining and tracking SLIs, SLOs, and SLAs.
• Lead incident response, root cause analysis, and blameless postmortems to reduce operational toil and improve MTTR.

FinOps, Cost Governance & Security

• Continuously monitor and optimize cloud costs (compute utilization, storage lifecycle, GPU usage, and data transfer) using AWS Cost Explorer, Budgets, Trusted Advisor, CloudHealth, or Kubecost.
• Implement AWS security best practices for IAM, VPCs, security groups, NACLs, encryption, and manage secrets using KMS, SSM Parameter Store, or Vault.
• Build secure CI/CD pipelines with automated security checks, least-privilege access, audit logging, and ensure compliance readiness for ISO 27001, SOC2, and GDPR.

Collaboration, Leadership & Platform Culture

• Work closely with engineering, AI/ML, QA, product, and operations teams to drive a DevOps, SRE, GitOps, and automation-first culture.
• Mentor junior DevOps and Platform Engineers while creating and maintaining detailed runbooks, architecture diagrams, and platform documentation.

Skills & Qualifications

Must-Have:

• 7+ years of experience in DevOps, SRE, Platform Engineering, or Cloud Infrastructure Engineering.
• Strong expertise in AWS cloud architecture, services, and deep understanding of Kubernetes (EKS), containers, and cloud-native systems.
• Strong Infrastructure-as-Code expertise using Terraform, CloudFormation, or CDK. Strong Linux administration, networking, DNS, routing, and load balancing knowledge. Strong scripting/programming experience in Python, Bash, or Go (preferred). Experience with CI/CD automation, GitOps workflows, and observability platforms supporting scalable production systems.

Preferred / Nice-to-Have:

• Experience with AI/ML infrastructure, MLOps, model serving, vector databases, GPU orchestration, and inference optimization.
• Familiarity with Kafka, Redis, SQS, and event-driven systems.
• Exposure to platform engineering, internal developer platforms, and tools like ArgoCD, Flux, Helm, and OpenTelemetry.
• AWS Certifications: Solutions Architect, DevOps Engineer, or SysOps Administrator. Knowledge of distributed systems and large-scale platform operations. 

Preferred / Nice-to-Have:

• Experience with AI/ML infrastructure, MLOps, model serving, vector databases, GPU orchestration, and inference optimization.
• Familiarity with Kafka, Redis, SQS, and event-driven systems.
• Exposure to platform engineering, internal developer platforms, and tools like ArgoCD, Flux, Helm, and OpenTelemetry.
• AWS Certifications: Solutions Architect, DevOps Engineer, or SysOps Administrator. Knowledge of distributed systems and large-scale platform operations. 

Here are answers to some questions you may have

Where is your office?

Chennai (Velachery)

Work Model

Work from Office – because great stories are built in person!

Do you have an online presence?

https://amura.ai (we are @AmuraHealth on all social media)

Read This Before Anything Else

We have 6 developers who can ship. What we don't have is someone who turns that into a real engineering function: real architecture, real leverage, real AI-driven advantage. If that gap sounds like an opportunity rather than a headache, you're in the right place. If it sounds like a lot of undefined work with no playbook handed to you, this one probably isn't for you. That's completely okay. There are plenty of great roles that fit differently.

About CraftMyPlate

CraftMyPlate is Hyderabad's go-to platform for food experiences for micro-events: house parties, birthdays, office celebrations, festive gatherings, and more. We're building the operating system for how India discovers, customises, and orders food for smaller events. We're backed by established founders and investors, and we're funded and growing fast. The next phase of that growth runs through engineering.

Where We Stand

Some numbers, because they matter more than adjectives. Order volume has grown 50x in two years, and we're compounding at roughly 3x year over year, without giving up equity to fund it. That means the business runs on its own economics. The growth is real demand, not runway bought with dilution, and every efficient architectural decision this role makes directly protects that.

Most people size up an opportunity by asking what's going to change in ten years. The more useful question, and the one this company is built around, is what won't change. People will keep gathering. They'll keep celebrating, hosting, and marking festivals, in 10 years and in 20. That permanence is the bet. You're not building infrastructure for a trend cycle. You're building for a category that outlasts the current AI wave, the next funding round, and probably us too.

The Technical Reality

Here's an honest read of the engineering problem, not a sanitized version of it.

Event-driven commerce doesn't scale like typical e-commerce. Demand isn't smooth, it's spiky: weekends, festival calendars, and event dates create real load concentration, and each order is tied to a hard deadline that can't slip the way a shipped package can. That has direct architectural consequences: systems need to handle bursty, unpredictable traffic without paying for idle capacity the rest of the time, which is exactly why we're serverless-first on AWS rather than running a fixed fleet sized for peak.

Underneath that, every order touches multiple systems that have to stay consistent: kitchen and vendor fulfillment status, inventory across partners, payment gateway settlement, and refunds, often in real time and often across more than one vendor for a single event. Getting that consistency right across SQL and NoSQL stores, without it becoming a source of support tickets and manual reconciliation, is a real architecture problem, not a CRUD problem.

The AI-agent layer is the next lever, and it's a business lever as much as a technical one. Every workflow we can hand to a well-orchestrated agent instead of a new hire is a workflow that scales without adding headcount, which is exactly how a company grows 3x a year without diluting equity to fund the team behind it. That's why agent orchestration across multiple LLMs, using LangGraph, sits in the "go deep" tier of this role rather than being a nice-to-have.

You'll likely find some of this framing right and some of it worth challenging once you're actually in the codebase. That's expected, and honestly preferred over someone who just nods along.

Why This Role Exists

You'll be the most senior technical person in the company, reporting directly to the founder. Not a manager brought in to run standups. An owner. You set the architecture, you write code yourself, and you make the team materially better. You also own where AI and automation take this company next, starting with our first in-house AI agent product (details shared in the interview), and expanding from there into how the company runs, department by department: HR, finance, marketing, design, development, all sitting on an engineering layer that you design.

If you've outgrown a role where you plan but don't build, or where good ideas die in a committee, this is built to be the opposite of that.

What You'll Own

• Architecture, end to end. Scalable, cost-efficient systems from day one, not "fix it later" engineering. You own the decisions and their long-term consequences.
• Hands-on building. You are still writing code and shipping. This isn't a seat where you review other people's work all day. You lead by building.
• The engineering team. Directly manage, mentor, and level up our 6 developers. Build the technical bar, the review culture, and the calibration that lets the team ship independently.
• The AI-agent roadmap. Own the architecture behind our first AI agent product, then the broader strategy for AI agents and automation across every function in the company, with engineering as the layer underneath all of it.
• Team scaling. Build the next layer of leads under you so execution quality scales without you being the bottleneck.
• Technical accountability. When something breaks, you fix it. You don't escalate and wait.

Our Stack, and the Depth We Expect

Not everything on this list needs the same level of mastery. Some of it you need to own at an architectural level. The rest you need to be strong enough to build yourself, direct the team on, or delegate to AI agents with confidence.

Go deep here. This is where the real architecture decisions live, and where the business impact is highest:

• AWS, serverless first. You should be genuinely well versed in AWS application development, not just "have used AWS." You should be able to design and guide serverless architecture (Lambda, API Gateway, DynamoDB, Step Functions, and similar) as our default way of building, because our demand curve is spiky by nature and fixed infrastructure is money left on the table.
• TypeScript, our primary language across backend and frontend.
• Agent orchestration across multiple LLMs, using LangGraph. This is core to our AI roadmap and our path to scaling operations without scaling headcount. You own how it's architected, not just how it's used.

Working proficiency. Build it yourself, direct the team, or hand it to an AI agent and know if the output is right.

This Is You If

• You've built and shipped real production systems yourself, not just reviewed other people's architecture from a distance.
• You go deep wherever the problem is, and you're comfortable owning the exact stack described above, not just "full-stack" in the abstract.
• You've made engineers around you measurably better, whether or not you've held the title for it yet.
• You're already using AI coding tools and agents seriously, like Claude, Cursor, or similar tools, as part of how you build, not as something you tried once. We'll likely explore this together in the interview.
• You have a bias toward leverage over hours. You'd rather automate or systematize a problem than grind through it. But when something's live and needs to be done right, you see it through completely, with no half-finished work.
• You want to build something for years, not land somewhere comfortable. We'll know the difference from how you talk about your last three years.

This Might Not Be the Right Fit If

• You'd prefer a stable, well-defined role with clear boundaries and someone else making the calls. That's a fair thing to want, just not what this is.
• You'd rather receive direction than bring us architecture and AI strategy yourself.
• You haven't yet gotten hands-on with AI coding tools in your daily work.
• You're drawn more to the title than the work behind it.

If none of that sounds like you, we'd love to hear from you.

Requirements

• 5 to 7 years of experience in software engineering, with real ownership of architecture-level decisions, not just feature delivery.
• Prior experience leading or mentoring engineers, formally or informally.
• Tier-1 or Tier-1+ engineering college strongly preferred (IIT, BITS, top NIT tier, or equivalent). We'll consider other institutions only with clearly commendable, verifiable work: real systems you can walk us through in depth, strong open-source contributions, or a track record that speaks for itself. Pedigree is a proxy for speed, not a checkbox. We test for the underlying ability regardless.
• Comfortable in an early-stage environment: undefined problems, few processes, and the expectation that you help define both.

Compensation

Competitive, with equity. We're formalizing a structured ESOP program alongside this hire. Specific numbers are discussed directly in later interview rounds.

If reading this got you a little excited about what you'd build here, we'd genuinely love to talk. If it didn't quite land, no hard feelings. We just want the right fit for both sides.

Role Overview

The Principal Architect leads Byteridge’s Technology Strategy & Solutions Group (TSS). This is a senior, visible role responsible for defining technology point-of-view, shaping solution narratives, guiding enterprise conversations, and influencing revenue through differentiated thinking.

The Architect owns thought leadership, reference architectures, solution accelerators, and selective engagement on high-impact deals.

Key Responsibilities

• Own, enhance & execute Byteridge’s technology strategy across priority areas (Cloud, Data, Gen AI, Modernization).
• Create and maintain enterprise-grade reference architectures, solution blueprints, PoCs and accelerators.
• Lead strategic discovery workshops and executive-level solutioning for priority opportunities.
• Partner with Content Marketing to translate technical POVs into blogs, whitepapers, decks, webinars, and sales narratives.
• Enable the Enterprise Account Executive with differentiated solution stories and technical credibility.
• Build strong partnerships with Byteridge delivery teams to identify high-impact solutions and projects that can be leveraged as compelling capability showcases for existing customers and prospective clients.
• Work with Delivery Team Architects to influence delivery standards and architectural consistency across teams.
• Research market and industry trends across technologies, popular enterprise solutions, and buyer adoption patterns. Go deep into selected domains and verticals to continuously refine Byteridge’s technology strategy, solution approaches, and positioning.
• Act as a visible external voice through talks, webinars, and published content.

Ideal Profile

• 13–20 years of experience across technology architecture, solutioning, or technology consulting roles.
• Demonstrated ability to research and synthesize market trends, emerging technologies, and popular enterprise solutions.
• Experience developing deep expertise in specific domains or industry verticals and translating that into solution strategies.
• Strong background in modern software engineering, cloud platforms, data, AI, and enterprise systems.
• Proven track record of influencing client decisions and shaping solution direction, not just designing systems.
• Comfortable working at the intersection of technology, business strategy, marketing, and sales.
• Excellent communication skills with executive presence and the ability to articulate complex ideas clearly.

Success Metrics (KPIs)

• Quarterly technology and market POVs produced and adopted internally or externally.
• Creation and reuse of reference architectures, solution frameworks, and accelerators across deals.
• Number of high-impact delivery projects converted into capability showcases and sales assets.
• Influence on strategic opportunities, measured through deal quality, size, and AE feedback.
• Thought leadership visibility through blogs, webinars, talks, or industry participation.
• Internal adoption of architectural standards and solution approaches by delivery teams.

Position Summary

We are looking for an experienced Enterprise Architect to define and deliver enterprise-scale digital experience architectures leveraging AI/ML capabilities, data platforms, and modern cloud technologies. The role involves partnering with senior business and technology stakeholders to translate business objectives into scalable architectures, strategic roadmaps, and technology solutions.

The ideal candidate will have strong expertise in enterprise architecture, cloud-native technologies, AI-driven customer experiences, and digital marketing platforms, along with the ability to lead architecture initiatives across cross-functional teams.

Key Responsibilities

• Enterprise Strategy & Roadmaps: Define digital, data, and AI strategies, translating business vision into actionable architecture roadmaps aligned with business goals and KPIs.
• Architecture Design: Design end-to-end enterprise and solution architectures integrating digital experience platforms, customer data platforms, AI/ML capabilities, and cloud services.
• Cloud & Technology Architecture: Recommend scalable, secure, and resilient architectures using cloud-native, API-first, microservices, event-driven, and serverless principles across Azure, AWS, or other public cloud platforms.
• AI & Data Architecture: Define architectures for customer data platforms, identity and profile management, data ingestion, governance, personalization, journey orchestration, and AI-powered experiences.
• Architecture Governance: Establish architecture standards, reference architectures, governance frameworks, and operating models to ensure consistency, security, and sustainable technology adoption.
• Stakeholder Management: Collaborate with business leaders, engineering teams, data architects, developers, and data scientists to drive architecture alignment and execution.
• Executive Communication: Lead architecture workshops, visioning sessions, and roadmap presentations, communicating technical recommendations and trade-offs to senior leadership.
• Practice Development: Contribute to reusable architecture assets, mentor architects and consultants, and support presales activities, solutioning, estimations, and proposals.

Required Skills & Experience

• Proven experience in enterprise architecture, solution architecture, and developing enterprise architecture models and roadmaps.
• Strong understanding of architecture frameworks and principles, including TOGAF, SOA, and API-led architecture.
• Hands-on experience with public cloud architecture and services, particularly Microsoft Azure and/or AWS.
• Experience designing and integrating AI-powered solutions, with knowledge of LLMs, prompt engineering, RAG, and model evaluation.
• Understanding of agentic workflows, tool-using agents, and enterprise AI governance, observability, and reliability.
• Experience working with software engineers, application developers, data architects, and data science/ML teams to deliver end-to-end solutions.
• Ability to translate business requirements and strategic vision into technical architectures and implementation roadmaps.
• Strong stakeholder management, leadership, presentation, and communication skills, including experience engaging with senior executives.
• Ability to lead architecture execution across multidisciplinary teams and communicate complex technical concepts to diverse audiences.

Good to Have

• Experience with Adobe Experience Cloud, Adobe Experience Platform, or one or more digital experience solutions.
• Previous experience with other digital marketing and customer experience platforms.
• Experience with customer data platforms, personalization, omnichannel engagement, and marketing optimization initiatives.
• Experience supporting consulting engagements, presales, and enterprise transformation initiatives.

Additional Requirement

- Willingness to travel up to 50%, depending on business and client requirements.

About the Role

We are looking for a Solution Architect with 10–15 years of experience to design scalable, secure, and cloud-ready solutions. The role involves working with customers, Senior Solution Architects, business analysts, project managers, and engineering teams across cloud, modernization, microservices, integration, and digital transformation initiatives.

Must Have Skills

• 10–15 years of experience in software development, architecture, and enterprise application delivery.
• Strong experience with Azure and/or AWS and cloud-native architecture.
• Hands-on experience with Microservices, REST APIs, SOA, and system integration.
• Experience in application modernization and cloud migration.
• Knowledge of Docker, Kubernetes, CI/CD, and Infrastructure as Code.
• Understanding of cloud security, IAM, networking, monitoring, and disaster recovery.
• Ability to create architecture diagrams, solution designs, and technical documentation.
• Strong analytical, communication, and customer-facing skills.

Good To Have Skills

• AWS/Azure certifications.
• Experience with Serverless, Event-Driven Architecture, Messaging, and API Management.
• Exposure to SaaS / Multi-Tenant Architecture.
• Knowledge of Generative AI and AI-enabled solutions.
• Experience with pre-sales, POCs, estimations, and technical proposals.
• Exposure to application security and compliance.
• Experience working with global customers and distributed teams.

Responsibilities

• Design end-to-end solutions and independently own defined architecture workstreams.
• Translate business and technical requirements into application, cloud, integration, and deployment designs.
• Define microservice, API, integration, and data-flow architectures.
• Guide engineering teams on architecture implementation and conduct design/code reviews.
• Contribute to cloud migration, modernization, and digital transformation initiatives.
• Participate in customer workshops, technical discussions, POCs, and solution demonstrations.
• Identify and address architectural, performance, security, and technical risks.
• Ensure solutions follow defined architecture, security, and engineering standards.
• Work closely with the Senior Solution Architect on complex and strategic engagements.
• Develop reusable architecture patterns, templates, and technical accelerators

Next

Bachelor's degree in Computer Science, Information Technology, or a related field (or equivalent experience).

3+ years of hands-on experience with Microsoft Azure, including IaaS, PaaS, networking, identity (Entra ID), and governance services.

2+ years of experience with DevOps tooling and practices, including CI/CD pipelines (Azure DevOps or GitHub Actions), Infrastructure as Code (Terraform, Bicep, or ARM), and version control (Git).

2+ years' experience in infrastructure design, platform engineering, or architecture.

Strong proficiency with automation and scripting — PowerShell, Azure CLI, Python, or Bash.

Solid understanding of containerisation (Docker) and familiarity with orchestration platforms (Azure Kubernetes Service).

Deep understanding of cloud architecture, deployment patterns, and management best practices, including the Azure Well-Architected Framework.

Experience defining standards, governance frameworks, and reference architectures for cloud platform consumption.

Strong knowledge of networking concepts, storage configurations, virtualisation technologies, and disaster recovery/backup design for hybrid environments.

Experience with Azure DevOps (Repos, Pipelines, Boards, Artifacts) or equivalent platforms.

Familiarity with identity and access management (IAM), including Entra ID, RBAC, PIM.

Strong understanding of security, compliance requirements, and IT governance frameworks (ITIL, COBIT, or similar).

Preferred

We’re on hunt for AI Architect

Responsibilities:

• 10–15+ years overall experience, with recent hands-on AI/GenAI architecture ownership.
• Must have architected enterprise AI platforms/solutions end-to-end, not just individual ML models or PoCs.
• Strong GenAI/LLM production experience: RAG, embeddings, vector DBs, hybrid search, reranking, evaluation, guardrails.
• Strong Agentic AI understanding: agents, tool calling, workflows, orchestration, human-in-the-loop.
• Experience taking AI solutions from architecture → production → scale, ideally across multiple business teams/use cases.
• Strong cloud architecture — Azure/AWS preferred; hybrid/on-prem experience is a plus.
• Must understand enterprise security, governance, Responsible AI, observability and LLMOps/MLOps.
• Should be able to articulate build-vs-buy, MVP-vs-target architecture, cost/performance/security tradeoffs.
• Strong stakeholder-facing / consulting ability — can work with business leaders, engineering, security and data teams and influence without authority.

There is scope to move to the US for this role if you are aligned for the same, else this will be a WFO role from Hyderabad location

Job Description: 

Lead regional transformation programs, driving the entire solution architecture lifecycle, 

from conceptualization to execution, with a focus on agile and DevOps practices. 

Accountable for leading the IT Architecture for all projects and programs, focusing on 

innovative business and IT solutions in the insurance domain, such as new-age digital 

platforms, cloud-native applications, AI/ML-powered decision-making, and data-driven 

insights.

Preferred skills  

• Demonstrated expertise in developing cloud-native, microservices-based, and API

driven insurance solutions, leveraging modern architectural patterns and emerging 

technologies such as AI/ML, big data, and IoT. 

• Thorough understanding of common patterns, frameworks, and reference 

architectures for the Insurance domain, with a focus on digital transformation and 

innovation. 

• Proven experience in leading regional transformation programs, driving the adoption 

of agile and DevOps practices. 

• Asia regional experience is an advantage.

Qualifications 

Minimum Bachelor's degree, preferably with a Master's degree in Computer Science, 

Engineering, or a related discipline. 

• 15+ years of IT experience, with a minimum of 7+ years in the insurance industry, 

focusing on the application of emerging technologies.

• Strong hands-on experience in Microsoft Azure Cloud.
• Good understanding of Azure services such as Compute, Storage, Event Hub, Event Subscription, Storage Queue, and PaaS services.
• Basic understanding of Azure AI Foundry and AI-related Azure service setup.
• Good Azure networking basics: VNet, subnet, routing, and basic troubleshooting.
• Strong knowledge of Terraform, especially:
• Terraform state
• plan / apply
• troubleshooting failures
• migration risks
• Terraform Enterprise concepts
• Strong Python coding capability, not just basic scripting.
• Experience using Python for API integration, automation, JSON/YAML handling, and internal tooling.
• Good understanding of CI/CD pipelines.
• Ability to troubleshoot pipeline failures.
• Comfortable with YAML and JSON.
• Ability to troubleshoot Azure infrastructure/platform issues.
• Ability to collect logs/evidence and coordinate with network/app/Microsoft support teams.
• Basic awareness of agentic AI / LLM concepts.
• Awareness of security and cost best practices.

Good to Have Skills

• Hands-on experience with Harness.
• Hands-on experience with Terraform Enterprise.
• Exposure to LangGraph / LangChain.
• Exposure to agentic AI workflows or skill creation.
• Exposure to Claude or enterprise LLM integrations.
• Knowledge of Azure ML Workspace, model registry, and managed endpoints.
• MLOps / LLMOps knowledge.
• FinOps / Azure cost optimization experience.
• Azure certifications: AZ-104, AZ-305, AZ-400, AZ-500.

Screening Priority:

Azure Cloud + Terraform + Python Coding + CI/CD Troubleshooting + YAML/JSON + Basic Agentic AI Awareness