Senior Solution Architect at AI tech startup · Remote only · 5 - 10 years · ₹15L - ₹23L / yr · Remote only · Posted 7 Jan 2026

Key Responsibilities
1. Platform & Application Architecture
- Architect and oversee end-to-end platform design using GCP services (Vertex AI, Cloud Run, GKE, Pub/Sub, Firestore, BigQuery, and IAM).
- Define the architecture for multi-tenant SaaS deployment—ensuring secure data boundaries across customers while maintaining a single codebase.
- Collaborate closely with backend developers to optimize Node.js APIs, data pipelines, and event-driven microservices.
- Design front-end integration flows and ensure UI/UX alignment with backend AI and agentic processes.
2. AI / LLM / Agentic System Architecture
- Lead architecture for all AI initiatives involving RAG pipelines, AI agents, NLP, and conversational AI.
- Evaluate and integrate LLMs and APIs from OpenAI, Google Gemini, Anthropic (Claude), Mistral, and others.
- Define frameworks for AI agent orchestration, prompt engineering, and function/tool calling workflows using frameworks like LangChain or LlamaIndex.
- Establish standards for vector databases (Pinecone, FAISS, Chroma), embeddings, chunking strategies, and retrieval optimization.
- Architect an AgentOps layer for monitoring, safety filtering, and AI model governance.
3. MLOps, PromptOps & DevOps Integration
- Implement CI/CD pipelines for AI models, prompts, and agents using Cloud Build, Terraform, and GitHub Actions.
- Design PromptOps and MLOps pipelines to manage model lifecycle, versioning, rollback, and production promotion.
- Define observability and monitoring mechanisms (OpenTelemetry, Cloud Monitoring, custom logs for LLM outputs).
- Collaborate with DevOps engineers to define blue/green and canary deployments across environments.
4. Security, Compliance & Scalability
- Design tenant-isolated data layers using IAM, VPC-SC, and KMS encryption policies to meet regulatory standards (HIPAA, GxP, GDPR).
- Implement data governance, access control, and threat detection mechanisms for AI-driven workflows.
- Create performance optimization strategies: GPU/TPU allocation, autoscaling policies, token budgets, response caching, and FinOps visibility.
5. Cross-Functional Leadership
- Partner with Product Managers and Business Analysts to translate business requirements into architectural blueprints.
- Work with UX/UI designers to ensure front-end experiences align with AI agent capabilities and backend APIs.
- Provide architectural guidance and technical mentorship to developers, ensuring adherence to best practices across projects.
- Contribute to platform evolution, reference architecture libraries, and reusable design patterns.
Key Skills & Qualifications
Technical Expertise
- Strong background in cloud architecture, specifically Google Cloud Platform (GCP)—Vertex AI, Cloud Run, Cloud Storage, IAM, Pub/Sub, BigQuery, VPC, and Cloud Functions.
- Proficiency with Node.js, TypeScript, and API development for scalable microservices.
- Deep understanding of LLMs, AI agent frameworks, retrieval-augmented generation (RAG), and vector search.
- Experience with LangChain, LlamaIndex, CrewAI, and Agentic AI design patterns.
- Strong understanding of data architecture, including NoSQL/SQL databases (MongoDB, Firestore, PostgreSQL).
- Hands-on experience with container orchestration (Docker, Kubernetes) and Infrastructure-as-Code (Terraform).
Preferred Skills
- Prior experience designing multi-tenant SaaS platforms.
- Exposure to frontend integration (Angular, React, or similar) and UI/UX flow understanding.
- Knowledge of AI safety, risk frameworks, and prompt governance.
- Strong analytical and communication skills for working across business and technical stakeholders.
- Awareness of FinOps and cost optimization in token-based AI ecosystems.
Qualifications
- Bachelor’s or Master’s degree in Computer Science, AI, or Cloud Architecture.
- 8–12 years of professional experience, with at least 3 years focused on AI platform architecture or enterprise-grade SaaS system design.
Certifications in GCP Professional Cloud Architect or Machine Learning Engineer are a plus.

Similar jobs (10)
Key Responsibilities
· System Design: Design secure, scalable, and highly available multi-tenant cloud-based application architectures.
· Integration Strategy: Build robust APIs, webhooks, and data pipelines for complex enterprise client connections.
· Technical Guidance: Mentor software engineers and lead critical code and architecture reviews to ensure engineering excellence.
· Performance & Security: Drive non-functional infrastructure needs including high uptime, strict data privacy compliance, and fast application response times.
· Cross-Functional Collaboration: Partner closely with Product, Security, and Customer Success teams to align technical execution with business roadmaps.
Required Qualifications
· Experience: 8+ years of experience in software engineering with at least 3+ years operating as a technical or solutions architect within a B2B SaaS environment.
· Cloud & DevOps: Deep production knowledge of major cloud infrastructure (AWS, GCP, or Azure), containerization technologies (Docker, Kubernetes), and modern CI/CD automation pipelines.
· Architecture Patterns: Proven expertise designing microservices, event-driven architectures, and high-performance relational and NoSQL database structures.
· Communication: Strong written and verbal communication skills, with a proven ability to translate complex technical concepts clearly to both engineers and business stakeholders.
· Education: Bachelor’s degree in Computer Science, Engineering, or a related field (or equivalent practical work experience).
Preferred Skills
· Prior experience managing architectural frameworks for enterprise compliance frameworks like SOC2, ISO 27001, or GDPR.
· Background in building real-time data processing engines, stream frameworks, or integrating enterprise AI/ML components.

Looking for an Architect with strong experience in AI and Data Engineering, preferably with hands-on experience in Generative AI (GenAI). Candidates with experience in any cloud platform (AWS, Azure, or GCP) will be considered,
Required Skills & Qualifications
- Experience: 10+ years in Cloud Engineering, Infrastructure, or DevOps, with strong hands-on GCP experience.
- GCP Expertise: GKE, Compute Engine, IAM, VPC, Cloud Storage, Cloud SQL, Cloud Run, Cloud Functions, and Load Balancing.
- Kubernetes & Containers: GKE, Docker, Kubernetes networking, Helm, and troubleshooting.
- DevOps & IaC: Azure DevOps, Terraform, CI/CD pipelines, and infrastructure automation.
- Scripting: Python, Bash, or PowerShell.
- Security & Operations: Cloud security, IAM, monitoring, incident management, and cost optimization.
- Leadership & Ownership: Proven experience in team leadership, cross-functional collaboration, stakeholder management, managing multiple product-line deliverables, and handling competing priorities and ad hoc requests.
- Additional Advantage: Experience with Microsoft Azure.
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.
Technical Architect – Product Engineering
Experience: 15+ Years
Location: Pune, India
Employment Type: Full-time
Desired Skills: Python, Technical Architecture, AWS, Microservices, SaaS / Multi-tenant Architecture, Kubernetes, System Design
About the Role
We are looking for a Senior Technical Architect to lead the architecture, design, and technical evolution of an enterprise SaaS product. This is a hands-on leadership role requiring deep technical expertise, strong product engineering experience, and the ability to build scalable, secure, and high-performance platforms.
The ideal candidate should be passionate about solving complex engineering problems, driving innovation, mentoring development teams, and effectively leveraging AI to accelerate software development.
Key Responsibilities
- Own the overall product architecture and technical roadmap.
- Design and build scalable, secure, and highly available enterprise applications.
- Lead the design and implementation of new product features from concept to production.
- Remain hands-on with coding and contribute to critical product components.
- Drive architecture reviews, code quality, performance optimization, and engineering best practices.
- Lead cloud architecture, security, scalability, and DevOps initiatives.
- Evaluate and adopt modern technologies to improve product capabilities and engineering efficiency.
- Leverage AI tools (ChatGPT, GitHub Copilot, Cursor, Claude, etc.) to accelerate software development, code reviews, testing, documentation, debugging, and productivity.
Required Skills & Qualifications
- 15+ years of software product engineering experience with at least 5 years in a Technical Architect role.
- Strong hands-on expertise in Python and modern backend frameworks.
- Deep experience with AWS services and cloud-native application architecture.
- Strong understanding of DevOps, CI/CD pipelines, Infrastructure as Code (Terraform/CloudFormation), Docker, Kubernetes, and container orchestration.
- Experience designing microservices, REST APIs, event-driven architectures, and distributed systems.
- Strong knowledge of SQL and NoSQL databases.
- Experience with scalable SaaS platforms, multi-tenant architectures, and secure application design.
- Excellent understanding of software design patterns, performance tuning, observability, and system reliability.
- Strong analytical, problem-solving, and decision-making skills.
Job Title : Senior AWS DevSecOps & AI Platform Engineer
Experience Required : 5+ Years in AWS / Cloud Engineering
Terraform Experience : 4+ Years
Location : Gurugram
Work Mode : Onsite
Employment Type : Full-time
About the Role :
We are looking for an experienced Senior AWS DevSecOps & AI Platform Engineer with strong expertise in AWS cloud infrastructure, Kubernetes, Infrastructure as Code (IaC), CI/CD automation, cloud security, and database administration.
The ideal candidate will be responsible for designing and maintaining secure, scalable, reliable, and cost-efficient cloud environments while supporting microservices-based applications and implementing DevSecOps best practices. The role also involves building and deploying AI agents using Amazon Bedrock and Bedrock AgentCore, along with managing enterprise development and collaboration tools.
Mandatory Skills :
AWS (EC2, EKS, ECS, Lambda, S3, CloudWatch), Kubernetes, Terraform, Jenkins, Bitbucket Pipelines, CI/CD, DevSecOps, AWS Security Services (IAM, WAF, GuardDuty, Security Hub, KMS, Secrets Manager), Microservices, Helm, PostgreSQL, Oracle SQL, RDS, Jira, Confluence, Amazon Bedrock, Bedrock AgentCore, AWS Networking, and Cloud Cost Optimization.
Key Responsibilities :
- AWS Cloud Infrastructure : Design, implement, and maintain AWS infrastructure with a focus on scalability, availability, security, reliability, and cost optimization.
- Microservices & Containerization : Manage and support distributed microservices architectures, including deployment, monitoring, troubleshooting, performance optimization, service meshes, and API gateways.
- Kubernetes Administration : Administer and optimize Kubernetes clusters, including Amazon EKS and self-managed environments, covering upgrades, networking, workload management, scaling, and resource optimization.
- Cloud Security & Compliance : Implement and manage AWS security services, including IAM, GuardDuty, Security Hub, WAF, KMS, Secrets Manager, AWS Config, and CloudTrail.
- DevSecOps Implementation : Integrate security testing, vulnerability scanning, container security, and compliance-as-code tools into CI/CD pipelines.
- CI/CD & Source Control : Manage Bitbucket repositories, branching strategies, permissions, and Bitbucket Pipelines. Build and optimize Jenkins pipelines using declarative and scripted approaches.
- Infrastructure as Code : Develop and maintain Terraform modules, manage remote state and workspaces, detect infrastructure drift, and implement reusable infrastructure provisioning practices.
- Database Administration : Provision, manage, secure, and optimize AWS RDS databases, particularly PostgreSQL and Oracle, including backups, replication, patching, performance tuning, and migrations.
- Jira & Confluence Administration : Manage projects, workflows, automation rules, permissions, user access, spaces, schemes, and plugins.
- Monitoring & Reliability : Define and monitor SLIs, SLOs, and SLAs; implement observability best practices; and participate in incident management, root cause analysis, and post-incident reviews.
- AI Agent Development : Design, build, and deploy AI agents using Amazon Bedrock and Bedrock AgentCore, including agent runtime, memory, tools, gateway integration, identity and access management, guardrails, and lifecycle management across environments.
- Cloud Connectivity : Support hybrid cloud connectivity using AWS Direct Connect, VPN, and Transit Gateway.
- Cost Optimization : Apply FinOps practices to monitor cloud expenditure, optimize resource utilization, and improve infrastructure efficiency.
- API Integrations : Integrate third-party APIs while implementing authentication, rate limiting, error handling, and webhook management.
Required Skills & Qualifications :
- 5+ years of hands-on experience with AWS cloud services, including EC2, ECS, EKS, Lambda, ALB, CDN, S3, CloudWatch, Amazon Bedrock, and Bedrock AgentCore.
- Strong understanding of AWS networking, multi-account strategies, landing zone architecture, and hybrid connectivity.
- 4+ years of practical experience with Terraform, including module development, remote state management, workspaces, drift detection, and state operations.
- Extensive experience administering Kubernetes, preferably Amazon EKS, including Helm, Kustomize, operators, RBAC, network policies, autoscaling, and multi-tenancy.
- Proven experience managing distributed microservices, service meshes, API gateways, and inter-service communication.
- Strong knowledge of AWS security services, including IAM, Service Control Policies (SCPs), WAF, KMS, Secrets Manager, AWS Config, and CloudTrail.
- Experience implementing least-privilege access, zero-trust principles, and cloud security compliance controls.
- Hands-on experience integrating DevSecOps tools such as Snyk, Trivy, Checkov, and SonarQube into CI/CD pipelines.
- Understanding of OWASP security principles, CIS benchmarks, vulnerability management, and container security.
- Proficiency in Bitbucket repository administration, branch permissions, and YAML-based Bitbucket Pipelines.
- Strong experience developing and maintaining Jenkins CI/CD pipelines, shared libraries, plugins, and build agents.
- Experience administering AWS RDS databases, particularly PostgreSQL and Oracle SQL, including backup, replication, performance tuning, and migration activities.
- Experience administering Jira and Confluence, including workflows, permissions, automation, and plugin management.
- Working knowledge of Azure services, particularly Web Apps and Logic Apps/Workflows.
- Practical experience with Amazon Bedrock, including model invocation, guardrails, and AI agent development and deployment using Bedrock AgentCore.
- Understanding of third-party API integration, authentication mechanisms, rate limiting, error handling, and webhook management.
- Familiarity with FinOps practices and cloud cost optimization.
Good-to-Have Skills :
- Additional Azure experience, including networking, Azure SQL Managed Instance, and Azure Kubernetes Service (AKS).
- Hands-on experience with AI-driven Development Lifecycle (AI-DLC) methodologies and tools such as Kiro.
Relevant certifications, such as :
- AWS Certified Solutions Architect
- AWS Certified DevOps Engineer – Professional
- AWS Machine Learning or Generative AI certifications
- Certified Kubernetes Administrator (CKA)
- HashiCorp Terraform certifications
Ideal Candidate Profile :
The ideal candidate is a hands-on cloud and DevSecOps professional who can manage enterprise-scale AWS infrastructure, automate deployments, strengthen security controls, troubleshoot complex distributed systems, and support AI agent development. Strong problem-solving skills, an automation-first mindset, and the ability to collaborate across development, security, and infrastructure teams are essential.

Role & Responsibilities
- Own end-to-end architecture, system design, development, and production deployment of scalable, AI-powered applications.
- Architect and develop high-performance backend services using Node.js, NestJS, TypeScript, Express.js, and Go.
- Design scalable web applications using React.js and Next.js, and cross-platform mobile applications using Flutter and Dart.
- Design distributed systems, microservices, event-driven architectures, and real-time applications capable of handling massive data volumes and high concurrent traffic.
- Design and optimize PostgreSQL/MySQL databases, MongoDB, Redis caching, database indexing, transactions, and query performance.
- Build real-time ride-booking, driver-allocation, location-tracking, and proximity-based matching systems using geospatial technologies such as PostGIS.
- Design and implement REST APIs, WebSockets, secure authentication, authorization, RBAC, and third-party integrations.
- Build and integrate Generative AI applications, LLM-powered chatbots, AI agents, RAG pipelines, embeddings, vector databases, tool calling, and intelligent automation workflows.
- Develop AI and backend services using Python and integrate LLM platforms such as OpenAI, Claude, and Gemini.
- Architect secure payment integrations, transaction workflows, webhook processing, idempotency, and payment reconciliation.
- Design and implement cloud-native infrastructure using AWS, Docker, CI/CD pipelines, and production monitoring tools.
- Ensure application security, scalability, reliability, performance, maintainability, and cost efficiency.
- Lead technical decision-making, code reviews, debugging, performance optimization, documentation, and mentoring of developers.
- Independently own critical engineering deliverables and drive products from concept and architecture through development, testing, deployment, and production support.
Preferred Candidate Profile
- 710+ years of software development experience, with substantial hands-on experience in technical architecture and production-grade application development.
- Expert-level proficiency in Node.js, NestJS, TypeScript, REST APIs, backend architecture, and microservices.
- Strong experience with React.js, Next.js, and modern frontend architecture.
- Hands-on experience with Flutter and Dart for Android and iOS application development.
- Proven experience designing scalable systems, handling large data volumes, concurrent workloads, and performance-critical applications.
- Strong experience with PostgreSQL, database design, indexing, query optimization, transactions, Redis, and geospatial systems.
- Practical experience building and deploying LLM-powered applications, AI agents, RAG systems, embeddings, vector search, and AI workflow automation.
- Proficiency in Python for AI integrations and backend services; Go language experience is highly desirable.
- Strong understanding of authentication, authorization, application security, payment integrations, and secure API design.
- Hands-on experience with AWS, Docker, CI/CD, Git, production deployments, logging, and monitoring.
- Familiarity with Kafka/RabbitMQ, Kubernetes, LangChain/LlamaIndex, and event-driven architectures is an advantage.
- Exceptional system-design, analytical, debugging, and problem-solving skills.
- Strong ownership, independent execution, technical leadership, communication, and mentoring abilities.
- Experience in startups or building products from scratch is highly desirable.
What We Expect
We are looking for a highly hands-on technical leader who can independently architect, design, develop, optimize, and deploy complex production systems. The ideal candidate must demonstrate genuine technical depth, strong engineering judgment, and the ability to lead end-to-end product development across backend, web, mobile, cloud, and AI technologies.
About the role
You will be a pivotal member of the leadership team, responsible for driving the company's product and platform strategy while overseeing engineering excellence across AI, data, platform, DevOps and infrastructure. This is a mission-critical role for an engineering leader who is both strategic and hands-on, and who can build scalable technologies for global enterprise clients in a fast-paced innovation ecosystem.
Reports to: CEO · Location: Bengaluru, India — hybrid, 3 days a week in office
What you will do
Technology & product leadership
- Define and drive the technology vision, architecture and long-term platform roadmap.
- Oversee the architecture, design and delivery of highly scalable enterprise systems.
- Ensure engineering excellence, velocity and reliability across the product lifecycle.
Engineering & platform management
- Lead platform engineering, product technology, DevOps, infrastructure and Quality Engineering.
- Build robust cloud-native systems using the Azure, AWS and GCP ecosystems.
- Oversee operational effectiveness, including uptime, production reliability and cost optimisation.
Innovation & AI strategy
- Spearhead Mission AI by developing scalable, production-grade AI/ML and GenAI capabilities.
- Own the GenAI/LLM solutions architecture.
- Core specialisation in AI agents and autonomous workflows, data extraction and intelligent automation.
- Direct hands-on architectural oversight of large language models, applied AI and multi-layered deep learning products.
- Extensive expertise in building intelligent document automation systems — similar in complexity to patent parsing, legal workflow automation and structured decision intelligence tools.
Technical leadership
- A proven track record overseeing product architecture, tech strategy and cross-functional engineering execution across core full-stack and AI platforms.
- Collaborate with executive leadership on business strategy, client requirements and product delivery.
- Build, mentor and scale high-performing engineering teams with a growth mindset.
- Establish a strong technology culture grounded in ownership, innovation and continuous learning.
What success looks like
- Mission AI: build a world-class AI system leveraging GenAI, ML and enterprise-grade data engineering.
- Hyper-scaling: architect and scale the platform to match global industry leaders in the IP space.
- Culture building: develop a strong engineering organisation with high ownership, performance and innovation DNA.
Qualifications & experience
- Preferably under 15 years of enterprise software engineering experience across B2B SaaS or technology-first companies; fewer is fine for an exceptional engineer.
- A proven track record of taking early-stage AI/ML prototypes and scaling them into robust enterprise SaaS platforms featuring multi-agent orchestration, complex workflows and decision intelligence.
- Experienced in building and mentoring agile, lean startup teams of full-stack and machine learning engineers from the ground up.
- Proven leadership in defining and executing technology strategy and platform roadmaps.
- Extensive cloud-native engineering experience with Azure, AWS and GCP.
Technical expertise
- Strong full-stack engineering background (Java, Python, JavaScript frameworks).
- Expertise with JS frameworks such as React, Angular and Node.js.
- Experience building and scaling distributed systems and microservices.
- Strong knowledge of databases (SQL, NoSQL), data modelling and unstructured data management.
- Strong understanding of Agile methodologies and tools (Atlassian, Git, CI/CD pipelines).
Behavioural & leadership competencies
- Product and delivery management expertise, end to end, including delivery and customer support.
- Excellent communication, with the ability to influence executive stakeholders.
- High technical proficiency combined with strong business acumen.
- Strong analytical and decision-making skills.
Senior Cloud Site Reliability Engineer (CSRE) – Azure
About Searce:
Searce is an AI-native, engineering-led modern technology consultancy that empowers
clients to futurify their businesses by delivering real, intelligent business outcomes. As a
trusted partner for over 3,000 clients globally, Searce specializes in cloud modernization,
data engineering, applied AI, and robust cloud platform security. Driven by a "HAPPIER"
cultural mindset and our proprietary evlos problem-solving framework, we eliminate
bureaucratic fluff to build working prototypes fast and scale enterprise production
environments intelligently. We don't just fix systems; we leverage multi-cloud technologies
to transform client operations into distinct competitive advantages.
Position Overview:
We are looking for a high-caliber Senior or Lead Cloud Site Reliability Engineer (CSRE) to
architect, secure, and stabilize next-generation hybrid and multi-cloud environments.
Operating at the intersection of infrastructure design, security compliance, and production
operations, you will serve as the technical Subject Matter Expert (SME) across GCP, Azure,
and AWS.
Whether optimizing a microservice mesh on GKE, tuning autoscaling on AKS, or driving a
massive disaster recovery drill across AWS regions, your focus will be absolute reliability. For
the Lead path, you will couple this deep engineering toolkit with stakeholder management
and mentorship to drive an elite operational culture.
Experience & Level Expectation:
Years of Experience: 3 to 10 years of intensive, hands-on production operations
experience in a dedicated DevOps, Cloud Platform Engineering, or SRE role.
Associate level (3-5 Years): Expected to show flawless execution of IaC, advanced
triaging of infrastructure failures, and ownership of the CI/CD and deployment
lifecycles.
Intermediate level (5-10 Years): Expected to take architectural ownership, serve as
primary Incident Commander for complex outages, design cross-cloud governance
frameworks, and act as a reliable bridge between technical teams and client
leadership.
Key Responsibilities & Role Expectations:
Multi-Cloud Platforms & Orchestration: Design, configure, and maintain
production-grade Kubernetes clusters across major platforms (AKS).
Manage advanced network routing, service meshes (e.g., Istio), and multi-tenant
isolation.
Infrastructure as Code (IaC) & GitOps: Build declarative, enterprise-grade, reusable
infrastructure components using Terraform or Crossplane. Standardize automated
environment provisioning to eliminate configuration drift across multi-branch
environments.
Incident Management & Reliability (SRE): Own and optimize the production on-call
rotation. Lead rapid mitigation strategies for Sev-1/Sev-2 system outages, reducing
Mean Time to Recovery (MTTR) through centralized log and metric correlation.
Root Cause Analysis (RCA): Facilitate rigorous, blameless post-incident reviews to
identify core architectural vulnerabilities and establish long-term fixes preventing
recurrence.
Lifecycle, Patching & Upgrades: Plan and execute zero-downtime cluster upgrades,
operating system patching strategies (Linux/Windows), database lifecycle updates,
and multi-region Disaster Recovery (DR) failover drills.
Core Core Operations & Legacy Integration: Manage enterprise-level hybrid
networking architecture (VPCs, Firewalls, Load Balancers, DNS routing, and DHCP
configurations) while effectively connecting cloud native services to legacy
infrastructures like Active Directory.
Security & Governance: Embed Zero Trust policies, secure secrets management
(Secrets Manager/Key Vault), and continuous vulnerability patching into the
automated SDLC pipeline.
Required Technical Skills:
- Microsoft Azure: Azure Virtual Machines, Virtual Networks, Azure Active Directory, Azure Update Management.
- Containers & Orchestration
- Production-level management of GKE, AKS, and EKS.
- Advanced mastery of Docker, Helm, Kubernetes StatefulSets, Pod Disruption
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
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