Cloud-Based Geocoding System Architect

What you'll need

• Bachelor's degree in Computer Science, Engineering, Information Systems, or a related technical field.
• 5+ years of professional data engineering experience.
• Experience designing and building cloud-native data solutions.
• Strong expertise with Google Cloud Platform, including BigQuery. Experience developing transformation frameworks using dbt.
• Strong SQL and Python programming skills.
• Experience with PostgreSQL or other relational databases.
• Experience orchestrating workflows using Apache Airflow or Cloud Composer.
• Experience implementing Infrastructure as Code using Terraform. Experience building CI/CD pipelines using GitHub Actions, GitLab CI, Jenkins, or similar platforms.
• Experience developing scalable batch and streaming data pipelines. Strong problem-solving skills with the ability to balance scalability, reliability, and cloud cost optimization.

Preferred Qualifications

• Experience with Pub/Sub, Datastream, Dataflow, Cloud Storage, Cloud Functions, or Cloud Run.
• Experience building multi-tenant SaaS platforms.
• Experience implementing metadata-driven governance, lineage, and data quality frameworks.
• Experience supporting AI, machine learning, or customer-facing analytics platforms.
• Experience with Kubernetes and Docker.

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).

About the Role

We are hiring Staff / Principal Engineers to take full, hands-on ownership of Blitzy's most critical production-grade systems and to deliver high-leverage features that materially improve customer outcomes and engineering velocity. This is the most senior individual contributor role at the company today.

This is not a Senior-plus role, an architecture-only role, or a promotion-track role. We are looking for someone who has already operated at Principal / Staff+ scope in a highly technical environment and expects to spend their time writing, reviewing, and shipping production code.

This role is 100% hands-on. Leverage comes from system ownership, execution quality, and durable technical decisions — not people management or process.

Responsibilities

• Own mission-critical production systems end-to-end, ensuring correctness, scalability, performance, reliability, and operational excellence.
• Design, build, and ship high-impact backend systems and features that improve product reliability, performance, and customer value.
• Architect scalable services and cloud infrastructure using technologies such as Python, REST, gRPC, Kubernetes, and Terraform.
• Identify and resolve complex technical bottlenecks that limit engineering quality, system performance, or organizational velocity.
• Build and operate LLM-powered systems and validation loops that evaluate correctness, consistency, durability, and production performance.
• Design and evolve data architectures incorporating relational, NoSQL, graph, and vector databases to support complex enterprise applications and semantic retrieval.
• Modernize and improve complex enterprise systems while balancing reliability, maintainability, scalability, and delivery speed.
• Set and uphold engineering quality standards through hands-on technical leadership, sound technical judgment, and ownership of long-term technical decisions.

Qualifications

• Direct experience with Python as a primary programming language, backend frameworks, and microservices architectures.
• Expertise in REST and gRPC, with proficiency in Node.js and JavaScript.
• Proficiency in GCP, along with experience using at least one additional cloud platform such as AWS or Azure.
• Advanced knowledge of Kubernetes and Terraform in production environments.
• Experience operating highly available production systems, including monitoring, scalability, reliability, performance optimization, and operational tooling.
• Strong knowledge of SQL and NoSQL databases, including PostgreSQL, MySQL, MongoDB, Cassandra, or DynamoDB.
• Familiarity with graph databases such as Neo4j and vector databases or embedding infrastructure for semantic search and retrieval.
• Hands-on experience building and operating LLM-powered systems in production, including evaluation, validation, regression testing, tracing, and failure analysis.
• Working knowledge of LangSmith or comparable LLM observability and evaluation tools; familiarity with OpenAI, Anthropic, or similar model providers is a plus.
• Ability to contribute across the full stack, with a strong understanding of frontend architecture and the ability to debug, design, and ship across frontend, backend, infrastructure, and AI systems.
• Understanding of large-scale enterprise software systems, including architecture, integration, deployment, modernization, and long-term maintainability.
• Proven track record of operating at Staff+, Principal Engineer, or equivalent level, independently driving complex technical initiatives and delivering high-impact outcomes with minimal supervision.

Blitzy is a Cambridge, MA based AI software development platform on a mission to revolutionize the software development life cycle by autonomously building custom software to unlock the next industrial revolution. We're transforming how enterprises build software, turning enterprise requirements into enterprise grade code with an agentic software development platform that can autonomously execute 80% of the quantum of software development work. We're backed by multiple tier 1 investors, and have proven success as founders of previous start-ups.

Our Culture

Who we are:

Led by two pioneering co-founders we are one of the fastest growing companies in the U.S., creating our own category of enterprise autonomous software development. We automate thousands of hours of software development for our customers, which includes strong representation within the Fortune 500.

How we work:

• We move Blitzy Fast: Time is both our company’s and our clients’ most precious asset. We move quickly and decisively to innovate internally and deliver exceptional software externally.
• Championship Mindset: We operate like a professional sports team. We win as a team by holding ourselves and each other to high standards, collaborating in-person, and remaining focused on the mission.
• Passion for Invention: We’re pushing the frontier of what’s possible, requiring constant innovation and iteration.
• We Work for the Customer: We focus on delivering outsized value to the customers we work with and expanding those relationships into deep, meaningful partnerships.
• We believe in being ‘everyday athletes’: taking care of ourselves so we can bring our best minds to work. We promote great sleep, movement, and restorative activities for 

Blitzy is an equal opportunity employer committed to building a diverse and inclusive team. We believe different perspectives make us stronger.

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.

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

Experience: 6+ years overall Data Engineering experience.

Must-have — candidates should have hands-on experience in ALL of these:

1. GCP (Google Cloud Platform) – strong hands-on experience
2. Python – data engineering/ETL development
3. SQL – advanced SQL, query optimization, data transformation
4. BigQuery – strong hands-on experience with development, optimization and data warehousing
5. Data Engineering / ETL – building and maintaining data pipelines
6. GCP data services – preferably Cloud Storage, Dataflow, Pub/Sub, Composer/Airflow, etc.
7. Data warehousing / dimensional modeling

Role Summary 

The GCP Delivery Lead is responsible for driving the technical vision, architecture, and delivery of enterprise-scale solutions on Google Cloud Platform (GCP). This role combines deep technical expertise with strong delivery leadership and customer engagement capabilities, working closely with clients, Google teams, and internal stakeholders. 

Key Responsibilities 

Technical Leadership 

• Define and own GCP solution architecture and technical strategy for client engagements 
• Design scalable, secure, and resilient cloud-native architectures 
• Establish architecture standards, best practices, and reusable frameworks 
• Provide governance and oversight across multiple programs 

Delivery Leadership 

• Ensure successful delivery of cloud transformation and modernization initiatives 
• Conduct architecture reviews, risk assessments, and quality assurance 
• Guide engineering teams through complex implementations 
• Ensure solutions meet performance, security, and scalability standards 

Google Partnership & Pre-Sales 

• Act as primary technical interface with Google Cloud teams 
• Support joint solutioning, co-selling, and client workshops 
• Contribute to proposals, solution design, and executive presentations 

AI & Data Solutions 

• Lead enterprise AI, GenAI, and data platform architecture on GCP 
• Drive adoption of Vertex AI, BigQuery, and modern AI/ML platforms 
• Advise clients on AI strategy, transformation, and innovation 

Practice Development 

• Build and mentor high-performing architecture and engineering teams 
• Drive certifications, capability building, and hiring initiatives 
• Create accelerators, reusable assets, and reference architectures 
• Contribute to practice growth and go-to-market strategies 

Required Qualifications 

Experience 

• 12+ years in cloud architecture, software engineering, or consulting 
• 5+ years of hands-on GCP architecture and delivery experience 
• Proven track record in large-scale cloud transformation programs 
• Experience managing multi-client and multi-program delivery 

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.

We're hiring a Cloud Architect (Contract) to work with our Equity Partners who builds profitable growth by acquiring and operating enterprise software companies. Refining a proprietary operating model across 40+ acquisitions and two decades of hands-on experience, now supercharged by our patented agentic AI platform . In this role, you'll take full architectural control of our CI/CD, observability, and event streaming infrastructure, build the standards every new acquisition plugs into, and use AI-assisted automation to keep 20+ products reliable without proportionally scaling headcount.

Job title: Cloud/Platform Architect (SRE)

Type: Global Remote | Contract

What You Bring

• 8–12 years in platform engineering, DevOps, or SRE, with growing ownership over time
• Deep Terraform experience across multi-account, multi-env setups
• Real production experience with event streaming at scale
• Hands-on Grafana, Prometheus, Loki, and strong AWS depth (ECS, EKS, IAM, VPC, RDS)
• SRE fundamentals: SLOs, error budgets, on-call design, post-mortems
• Bonus: acquisition or greenfield platform-building experience

Roles and Responsibilities

• Own everything outside core AWS infra: CI/CD, observability, event streaming, deployment, incidents
• Define the standards every future acquisition will plug into
• Keep 20+ enterprise products running at serious scale (millions–billions of requests)
• Build self-service tooling so product teams never wait on you
• Use AI/automation to kill toil — not to replace engineering judgement

Ready to build the platform that scales an entire portfolio? — let's connect.

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.