GCP Delivery Lead

AWS Delivery Lead

Location: Mumbai / Bangalore / Gurgaon / Hyderabad 

Role Summary 

The AWS Practice Lead is a senior technical leader responsible for driving AWS architecture, delivery excellence, customer engagement, and practice growth at AuxoAI. This role involves designing enterprise-scale cloud and AI solutions, leading cross-functional teams, and working closely with AWS stakeholders to position AuxoAI as a leading Enterprise AI and Cloud Transformation partner. 

Key Responsibilities 

1. Technical Leadership 

• Define and drive AWS architecture strategy across engagements 
• Design scalable, secure, resilient, and cost-effective solutions 
• Establish architecture standards, governance, and best practices 
• Lead architecture reviews and provide oversight on complex programs 

2. Delivery Leadership 

• Partner with delivery and account teams to ensure successful execution 
• Guide engineering teams on technical decisions and challenges 
• Ensure delivery quality aligned with AWS Well-Architected principles 
• Identify and mitigate risks across projects 

3. AWS Partnership & Customer Engagement 

• Act as the technical lead for AWS partnership initiatives 
• Collaborate with AWS teams on joint opportunities 
• Lead customer workshops, executive briefings, and solution design sessions 
• Support pre-sales, proposals, and technical presentations 

4. AI & Data Innovation 

• Lead AI/ML, Generative AI, and data analytics solutions on AWS 
• Architect modern AI applications using AWS services (e.g., Bedrock, SageMaker) 
• Advise customers on AI adoption, modernization, and data strategy 
• Drive innovations in GenAI, Agentic AI, and automation 

5. Practice Building 

• Build and mentor AWS architecture and engineering teams 
• Drive certifications and skill development 
• Create reusable frameworks, accelerators, and best practices 
• Support hiring and growth of the AWS practice 

Required Qualifications 

Experience 

• 12+ years in cloud architecture / consulting / enterprise technology 
• 5+ years of hands-on AWS architecture experience 
• Proven expertise in large-scale cloud transformation programs 
• Strong stakeholder management and consulting skills 

Technical Skills 

• AWS Core: EC2, S3, RDS, VPC, IAM, Route 53, ELB, Control Tower 
• Cloud Native & DevOps: EKS, ECS, Lambda, API Gateway, Terraform, CI/CD 
• Data & Analytics: Redshift, Glue, Athena, EMR, Kinesis 
• Security & Governance: Security Hub, GuardDuty, KMS, CloudTrail 
• AI/ML & GenAI: Bedrock, SageMaker, LLMs, RAG, vector DBs, MLOps 

Leadership Skills 

• Strong communication and executive presentation abilities 
• Experience leading workshops and influencing stakeholders 
• Proven team mentoring and leadership capabilities 
• Customer-centric mindset with strong business acumen 

Preferred Qualifications 

• AWS Certifications (Solutions Architect Professional, DevOps, ML, Security) 
• Experience with AWS Partner Network (APN) and co-sell programs 
• Multi-cloud exposure (Azure/GCP) 
• Experience delivering AI/GenAI solutions for enterprise clients 
• Exposure to regulated industries (BFSI, Healthcare, Telecom, etc.) 

Success Metrics 

• Successful delivery of strategic AWS engagements 
• Growth in AWS services revenue and customer satisfaction 
• Expansion of AWS partnerships and go-to-market initiatives 
• Increase in AWS-certified talent and reusable solution assets 
• Establishment of AuxoAI as a trusted AWS & AI transformation partner 

GCP Data Engineering Lead

Experience: 9+ Years

Lead Experience: 2+ Years

Location: Bangalore / Hyderabad

Key Skills:

• Strong experience in GCP Data Engineering and BigQuery
• Hands-on experience with Oracle Exadata / PL-SQL
• Strong knowledge of PySpark / Scala and Python
• Experience with GoldenGate, Kafka and CDC
• Hands-on experience with Apache Airflow
• Good experience in CI/CD and DevOps practices
• Experience with Terraform / Infrastructure as Code
• Exposure to AI/LLM technologies and GenAI solutions
• Strong understanding of data architecture, ETL/ELT and data pipelines

Roles & Responsibilities:

• Lead the design and development of scalable GCP data engineering solutions.
• Design and implement batch and real-time data pipelines using BigQuery, PySpark, Kafka/CDC and Airflow.
• Work with Oracle Exadata/PL-SQL and GoldenGate for data integration and migration.
• Implement CI/CD pipelines and infrastructure automation using Terraform.
• Explore and integrate AI/LLM capabilities into data engineering solutions.
• Lead technical discussions, code reviews, solution design and mentor team members.
• Collaborate with business and technical teams to deliver high-quality data solutions.

Platform Engineering Lead (For client company)

Location: Pune, India

Experience: 7+ years 

What Success Looks Like

• Engineering teams ship faster with confidence and built-in guardrails.
• Cloud cost, security, and reliability are predictable, measurable, and well-managed.
• CI/CD pipelines are trusted, standardized, and production-ready.
• Platform decisions reduce cognitive load instead of introducing unnecessary process. 

Scope & Expectations

This is a hands-on leadership role combining architecture and implementation.

You will:

• Build, not just review.
• Own the platform roadmap—not just infrastructure tickets.
• Act as a force multiplier for product engineering teams rather than becoming a bottleneck.
• Drive platform strategy while remaining deeply involved in execution.

Key Responsibilities

Platform & Cloud Architecture

• Own Zoop's platform and cloud architecture across GCP and AWS.
• Design reusable, opinionated platform patterns instead of one-off infrastructure.
• Build and evolve Zoop's Internal Developer Platform (IDP), including:
• Self-service environments
• Golden paths (paved roads)
• Standardized templates
• Built-in engineering guardrails
• Lead Kubernetes and cloud-native adoption at scale.
• Drive infrastructure automation using Terraform, Pulumi, or similar Infrastructure-as-Code (IaC) tools.

CI/CD, Reliability & Developer Experience

• Establish robust CI/CD practices with quality gates and production readiness.
• Improve deployment safety through automation and testing.
• Define and monitor:
• Golden Signals
• SLIs
• SLOs
• Incident response processes
• Reduce operational toil and improve developer productivity.
• Make observability a first-class capability using cost-efficient monitoring systems.
• Build an observability platform that multiple engineering teams can easily integrate into their applications.

Security, Privacy & Compliance

• Build security-by-default into infrastructure and deployment pipelines.
• Lead implementation and continuous compliance for:
• DPDP Act (India)
• ISO 27001:2022
• SOC 2 Type II
• Implement:
• Zero Trust architecture
• Least-privilege access
• Secure data isolation

FinOps & Cloud Optimization

• Make cloud costs transparent and accountable across engineering teams.
• Establish FinOps practices including:
• Budgets
• Cost alerts
• Optimization routines
• Drive build-vs-buy decisions using clear ROI analysis.

AI, Data & MLOps Foundations

• Build secure and scalable foundations for AI and MLOps workloads.
• Define guardrails for AI systems and sensitive data handling.

Leadership & Collaboration

• Partner closely with engineering teams to align infrastructure strategy with product goals.
• Mentor engineers and guide teams through technical change.
• Balance long-term platform initiatives with practical execution.

What We're Looking For

Experience

• 7+ years of experience building and operating production infrastructure.
• Experience scaling engineering platforms in high-growth or regulated companies.
• Strong hands-on expertise in:
• Kubernetes and the cloud-native ecosystem
• Service Mesh technologies
• Policy Engines
• GCP, AWS (Azure exposure is a plus)
• Terraform and Infrastructure as Code

Engineering & Operations

• Strong understanding of SDLC and modern CI/CD systems (Jenkins, GitOps, etc.).
• Experience with observability tools such as:
• Grafana
• Prometheus
• New Relic
• Comfortable reading and contributing to production systems written in:
• Go
• Python
• Node.js

Security & Compliance

• Practical experience implementing ISO 27001 and SOC 2 controls.
• Strong understanding of:
• Data protection
• Privacy
• Identity and access management
• Security best practices

Mindset

We're looking for someone who is:

• Action-oriented with sound engineering judgment.
• Analytical, cost-conscious, and reliability-focused.
• Collaborative, calm under pressure, and open to feedback.
• Comfortable challenging decisions and explaining trade-offs when necessary.

Nice to Have

• Experience in fintech, identity, or other regulated industries.
• Built Internal Developer Platforms (IDPs) or shared infrastructure tooling.
• Contributions to open-source projects.

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.

About the Company

As the world moves toward AI-native applications, one element matters more than anything: data.

We are building a platform that helps organizations unlock the value hidden within customer feedback. By centralizing data from multiple sources—including CRM platforms, support systems, collaboration tools, surveys, community forums, and customer conversations—into a unified intelligence layer, we enable teams to understand customer needs and make better product decisions.

Built on top of this foundation is an AI-powered platform that allows teams to query, monitor, and act on customer intelligence directly within their workflows. Our customers include some of the fastest-growing product-led technology companies as well as large global enterprises.

Backed by leading global venture capital firms, our engineering culture is AI-native from the ground up. Agents, LLMs, and applied machine learning are not side projects—they are central to how we build products. We operate at the cutting edge of agentic systems and continuously push the boundaries of what modern AI applications can achieve.

What You Will Do

• Convert product direction into phased technical plans, including estimates, milestones, dependencies, and risk assessments.
• Make thoughtful trade-offs across correctness, latency, user experience, AI/model behavior, reliability, cost, and delivery speed.
• Define clear ownership boundaries across frontend applications, BFF layers, backend services, agent workflows, ML platforms, and data contracts.
• Review ERDs, PRDs, design documents, and implementation plans to identify gaps before they become execution challenges.
• Drive planning and execution for complex initiatives while empowering area leads and senior engineers to maintain ownership.
• Partner closely with Product, Design, Engineering, and GTM teams to turn ambiguous problem statements into executable solutions.
• Influence technical direction through strong engineering judgment, architectural leadership, and hands-on involvement.
• Mentor senior engineers and contribute to engineering excellence through reviews, incident analysis, and proactive risk management.

What It Takes

• 5+ years of experience as a Senior Engineer, Technical Lead, or equivalent role.
• Demonstrated experience owning architecture and execution for large-scale product or platform initiatives spanning multiple teams.
• Strong foundation in distributed systems and modern software architecture.
• Exposure to agentic AI systems, machine learning engineering, MLOps platforms, and frontend/BFF architectures.
• Ability to own end-to-end product and technical problems rather than specializing exclusively in a single layer of the stack.
• Proven track record of converting ambiguity into actionable engineering plans.
• Excellent written communication skills, including design documentation, architectural reviews, trade-off analyses, and RCA documentation.
• Ability to challenge requirements constructively and collaborate effectively across Product, Design, Engineering, and GTM functions.
• High ownership mindset, attention to detail, and a low-ego, collaborative approach.

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).

Experience: 5+ Years

Employment Type: Full-Time

Role Overview

We are looking for an experienced GCP Data Engineer with 5+ years of experience in data engineering and strong hands-on expertise in Google BigQuery, Google Cloud Storage (GCS), Airflow/Cloud Composer, Python, and Vertex AI. The candidate should be capable of designing, developing, and maintaining scalable data pipelines and cloud-based data solutions on Google Cloud Platform.

Key Skills – Mandatory

• BigQuery – Strong hands-on experience in data warehousing, SQL, optimization, and performance tuning.
• Google Cloud Storage (GCS) – Experience with data storage, file management, and integration with data pipelines.
• Airflow / Cloud Composer – Experience in developing, scheduling, monitoring, and managing data workflows.
• Python – Strong programming skills for data engineering, ETL/ELT development, automation, and pipeline implementation.
• Vertex AI – Experience working with ML/AI workflows, model integration, or data pipelines supporting AI/ML solutions.

Good to Have / Added Advantage

• Dataproc – Experience with distributed data processing and Spark-based workloads.
• Cloud Data Fusion – Experience in building and managing data integration pipelines.
• Cloud Run – Understanding of deploying and running containerized applications/services on GCP.
• Experience with ETL/ELT processes and data pipeline development.
• Knowledge of GCP data architecture and cloud-native services.
• Experience in data quality, validation, monitoring, and troubleshooting.

Responsibilities

• Design, develop, and maintain scalable GCP-based data pipelines.
• Build and optimize data solutions using BigQuery and Cloud Storage.
• Develop and manage workflows using Airflow / Cloud Composer.
• Write efficient and reusable Python code for data processing and automation.
• Support Vertex AI integrations and AI/ML data workflows.
• Monitor pipeline performance and troubleshoot data processing issues.
• Work with cross-functional teams to understand data requirements and deliver reliable solutions.
• Implement best practices for data security, quality, scalability, and performance.

You must have :

• 5+ years of overall experience in Data Engineering.
• Strong hands-on experience with BigQuery, GCS, Airflow/Cloud Composer, Python, and Vertex AI.
• Strong understanding of data engineering concepts, ETL/ELT, data pipelines, and cloud technologies.
• Dataproc, Data Fusion, and Cloud Run experience will be an added advantage.

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.

15+ years of IT Delivery and Technology Services experience.

15+ years managing large offshore delivery organizations.

Proven leadership of portfolios exceeding 200+ resources.

Financial Services or Banking experience is a MUST

Extensive technical experience in Data Engineering, Data Platforms, Data Brics.

Cloud Data Transformation Programs, Data Warehousing, Azure Data Platform and compliance experience

About Searce

Searce is a global, AI-native, engineering-led technology consultancy and a Premier Google

Cloud Partner — recognized as the Google Cloud Workplace AI Transformation Partner of the

Year, APAC (2026). With 20+ years of experience and 3,000+ clients across 10+ countries, we

help businesses stay ahead of the cloud curve.

The Role

We're looking for a Lead Cloud Security & Reliability Engineer with deep GCP expertise to own

end-to-end cloud reliability and security forAPAC enterprise clients. As Lead, you'll set the architectural direction, mentor your squad, and drive measurable client outcomes across multi-

cloud environments.

What You'll Do

Own Client Delivery — Lead 24x7 GCP cloud operations forAPAC clients. Define SLO frameworks and ensure adherence.

Architect Solutions — Design scalable, secure GCP-primary architectures with multi-cloud awareness.

Drive Reliability — Lead incident response, RCA, and long-term remediation across production systems.

Mentor & Elevate — Coach and grow a squad of Senior CSREs.

Drive FinOps — Own cloud cost governance and optimization with quantified impact.

Be the Expert — Represent Searce's technical depth in global client conversations.

What We're Looking For

Experience

7–12 years total with 5+ years on GCP cloud infrastructure

Strong background in Cloud Managed Services / MSP environments

Proven experience leading a team in client-facing delivery

Multi-cloud exposure (AWS/Azure secondary) preferred

Technical Skills (Must-Have)

• GCP: GKE, IAM, VPC, Cloud Monitoring, Stackdriver, KMS — demonstrated in work
• experience
• Kubernetes: GKE — production cluster management, Helm
• IaC: Terraform — module-level, reusable frameworks
• Observability: Prometheus, Grafana, Thanos or equivalent
• Security: IAM, Zero-trust, DevSecOps, CSPM tools
• Scripting: Python or Go
• FinOps: GCP cost governance demonstrated

Nice to Have

• GCP Professional Cloud Architect / Pro DevOps Engineer certification
• AWS / Azure secondary experience
• CKA (Certified Kubernetes Administrator)
• ITIL / change management awareness
• APAC client delivery experience

Why Searce?

🏆 Google Cloud Partner of the Year — APAC 2026

🌍 Work with APAC enterprise clients across multiple industries

🤖 AI-first, engineering-led culture

📈 Lead-level ownership with real career growth

🤝 HAPPIER values — Humble, Adaptable, Positive, Passionate, Innovative, Excellence,

Responsible