Senior Solution Architect – Google Cloud (Vertex AI,

AI Architect – Enterprise AI & Generative AI ( Remote) - Contractual

Experience: 8+ years

Location: Remote, India

Employment Type: Contractual

Working Hours: 3:00 PM – 12:00 AM IST

Client Engagement: US-based client

About the Role

We are looking for a hands-on, client-facing AI Architect to lead the architecture, technical direction, and production implementation of enterprise AI and Generative AI solutions for a US-based client.

You should combine strong software engineering and cloud architecture fundamentals with practical experience building secure, scalable, and reliable AI applications. This role involves end-to-end technical ownership, from solution design and prototyping to production deployment and optimization. It is not a research-only, advisory-only, or prompt-writing position.

Key Responsibilities

• Lead end-to-end architecture and delivery of AI/ML and Generative AI solutions, from discovery and proof of concept to production rollout.
• Design LLM-powered applications using Retrieval-Augmented Generation (RAG), embeddings, vector databases, AI agents, and orchestration frameworks.
• Define data ingestion, chunking, retrieval, grounding, evaluation, and knowledge-refresh strategies.
• Select appropriate AI models and platforms based on quality, latency, cost, security, and operational requirements.
• Design cloud-native architectures, APIs, integrations, identity controls, monitoring, and resilient deployment patterns.
• Create architecture diagrams, technical designs, implementation roadmaps, and technical standards.
• Implement AI quality and safety measures, including hallucination mitigation, guardrails, access controls, and prompt-injection defenses.
• Guide engineering, data, ML, and DevOps teams through implementation, code reviews, troubleshooting, and go-live readiness.
• Lead technical discussions and design reviews with US client stakeholders.
• Establish production monitoring, CI/CD, versioning, incident handling, and performance and cost optimization practices.

Required Skills & Qualifications

• 8+ years of relevant experience in software engineering, AI/ML engineering, data engineering, or technology architecture.
• Proven experience personally architecting and deploying at least one enterprise-grade AI or Generative AI solution into production.
• Strong practical knowledge of LLMs, RAG, embeddings, vector databases, orchestration frameworks, and model evaluation.
• Hands-on experience with Python and APIs, including prototyping, code review, and troubleshooting.
• Experience with at least one major cloud platform: Microsoft Azure, AWS, or Google Cloud Platform (GCP).
• Understanding of data pipelines, SQL/NoSQL databases, containers, CI/CD, MLOps, and LLMOps.
• Knowledge of enterprise security, privacy, identity and access management, and responsible AI practices.
• Experience independently leading architecture workshops, design reviews, and technical discussions with US clients.
• Excellent written and spoken English, documentation, and stakeholder management skills.
• Availability to work from 3:00 PM to 12:00 AM IST and willingness to accept a contractual engagement.

Preferred Experience

• Azure AI Foundry, Azure OpenAI, Amazon Bedrock, or Google Vertex AI.
• Azure AI Search or equivalent retrieval tools.
• LangChain, LangGraph, Semantic Kernel, and agent/tool orchestration.
• Model fine-tuning, predictive ML, document intelligence, multimodal AI, or real-time AI applications.
• Experience in cloud modernization, enterprise integrations, data analytics, or technology consulting.
• Relevant AI/cloud architecture certifications and experience mentoring technical teams.

What Success Looks Like

• Designing secure, scalable, production-ready AI solutions rather than demos or conceptual presentations.
• Making sound technical decisions around feasibility, performance, reliability, cost, and AI risks.
• Taking ownership of architecture decisions and resolving technical blockers with limited supervision.
• Building trust with senior US stakeholders and collaborating effectively with India-based delivery teams.

Contract Details

• Initial engagement: Minimum 3 months, with extension subject to project requirements and performance.
• Working schedule: 3:00 PM – 12:00 AM IST.
• Potential permanent employment: After 18 months, the client may consider direct permanent employment at its sole discretion. Conversion is not guaranteed.

Mandatory Screening Criteria

Candidates should be able to:

• Explain an enterprise AI/GenAI solution they personally architected and deployed, including architecture, scale, evaluation, and business impact.
• Whiteboard an enterprise RAG or agentic solution covering data flow, security, authentication, authorization, monitoring, and cost controls.
• Discuss real-world model-quality issues, hallucinations, privacy risks, incidents, and architectural trade-offs.
• Lead a technical design review with US client stakeholders.
• Confirm acceptance of the working hours and contractual engagement.

Apply only if you have hands-on experience architecting and deploying enterprise AI/GenAI solutions in production.

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.

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.

• Senior Machine Learning Engineer – Vertex AI
• Senior Generative AI Engineer – GCP
• Google Cloud AI/ML Engineer
• MLOps Engineer – Vertex AI
• LLM Engineer – RAG, Gemini, and Vertex AI

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.

I’m a Google Cloud Data Engineer with 5+ years of experience in data engineering, ETL, and cloud data solutions. I specialize in BigQuery, Dataform, Cloud Composer (Airflow), SQL, and CI/CD automation.

I have hands-on experience building reusable Dataform frameworks, developing and orchestrating data pipelines, supporting cloud platform upgrades, implementing secure IAM access, and optimizing data transformation workflows. I’ve also worked on AI-assisted SQLX code generation to improve developer productivity and standardize development.

I’m passionate about building scalable, reliable, and efficient data solutions. I’m looking for opportunities where I can contribute my GCP expertise, solve real-world data challenges, collaborate with talented teams, and continue growing as a Data Engineer.

Core skills: Google Cloud Platform (GCP) | BigQuery | Dataform | Cloud Composer | Apache Airflow | SQL | Python | ETL | CI/CD | GitHub Actions | Dataplex

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

Senior Data Engineer – Ab Initio | GCP | Spark | Agentic AI

Location: Bangalore

Experience: 5+ Years

Role: Senior Data Engineer

Work Mode: Bangalore

Job Summary

We are looking for an experienced Senior Data Engineer with strong expertise in Ab Initio, GCP, Apache Spark, and Agentic AI. The ideal candidate will have hands-on experience designing and developing scalable data engineering solutions, building data pipelines, and working with modern cloud and AI technologies.

The candidate should be comfortable working across traditional enterprise data platforms and emerging Generative AI / Agentic AI solutions.

Key Responsibilities

• Design, develop, and maintain scalable and high-performance data pipelines using Ab Initio, Spark, and GCP services.
• Develop and optimize complex ETL/ELT workflows using Ab Initio.
• Build and maintain data processing solutions using Apache Spark / PySpark.
• Develop cloud-based data solutions on Google Cloud Platform (GCP).
• Work with GCP data services such as BigQuery, Cloud Storage, Dataflow, Dataproc, Pub/Sub, or equivalent services.
• Perform data integration, transformation, cleansing, and validation.
• Optimize data pipelines for performance, scalability, reliability, and cost.
• Collaborate with data architects,
• 
  

Build AI where the work actually happens.

Celeco works inside real businesses to understand critical workflows, ship production AI systems and stay through adoption.

We are hiring our first Intelligence Architect (Forward-Deployed AI Engineer).

⌁

Full-time · Remote-first · Optional hybrid in Bengaluru

At least one year of professional engineering experience. Customer travel when the work requires it.

The role

An Intelligence Architect enters a customer environment with an unfinished question and leaves behind a working, measurable system.

This is a hands-on engineering role at the boundary of product, operations and customer delivery. You will learn the domain, inspect the existing systems and data, decide what should be built, and write the code that puts it into production.

What you will own

• Interview and shadow the people doing the work, then map the real workflow, including hand-offs, exceptions and workarounds.
• Understand the customer's application stack, APIs, data, identity model, security constraints and deployment environment.
• Turn business goals into a technical scope, system design, delivery plan and measures of success.
• Build across the stack: AI workflows, data pipelines, integrations, backend services and the interfaces people use.
• Choose the simplest reliable approach. The answer may combine agents, retrieval, rules and conventional software.
• Create evals from representative cases, define quality and failure metrics, inspect traces, red-team the system and set launch thresholds.
• Make practical trade-offs across accuracy, latency, cost, privacy, security and speed.
• Take prototypes into production with tests, monitoring, access controls, documentation and a plan for failure and recovery.
• Work beside customer teams during rollout and improve the system until it becomes part of the workflow.
• Turn what works into reusable components, evaluation sets and playbooks for future Celeco deployments.

You will probably thrive here if

• You have at least one year of professional software or product engineering experience.
• You have shipped a real system used by other people and can explain what you owned, what broke and what you changed.
• You are strong in Python or TypeScript and comfortable moving across unfamiliar codebases, APIs, databases and cloud services.
• You have built with language or multimodal models and understand prompting, structured outputs, retrieval, tool use and model failure modes.
• You use Cursor, Codex, Claude Code or similar tools as part of your engineering workflow, while still reviewing, testing and understanding the code you ship.
• You can create an evaluation set, choose useful quality metrics and improve a system through error analysis instead of prompt guesswork.
• You can speak with an operator, an engineering team and a senior leader without losing the thread of the problem.
• You work well with incomplete requirements, write clearly and surface risks early.
• You care about whether people use what you build and whether it changes a business outcome.
• You can commit full-time and travel to customer sites when discovery or rollout is better done in person.

Experience with cloud deployment, containers, CI/CD, observability, enterprise integrations, authentication or security is useful. We do not expect one person to arrive knowing every framework, cloud or industry.

What you will get

• Direct ownership of live customer problems from discovery through production.
• Close collaboration with Celeco's founders and customer leadership teams.
• Exposure to different industries, operating models and technical environments.
• The freedom to choose the technical approach and the responsibility to prove that it works.
• A role in defining Celeco's engineering methods, reusable systems and technical culture while the company is early.
• A remote-first setup, with the option to work together in Bengaluru.

If the work sounds like you but your background is unconventional, apply. We care more about what you have built, how you think and how quickly you learn than pedigree.