SQUARESHIFT TECHNOLOGIES
Technical Architect
Location: Chennai, India (Hybrid) | Practice: Cloud, Data & AI | Reports to: Director of Engineering
SquareShift is a Google Cloud Premier Partner, Looker Delivery-Verified Partner, and Elastic Professional Services partner. We design and build production cloud, data, and AI/ML systems for ISVs, SaaS companies, and enterprises across the US and India.
Our work is technically dense — multi-tenant data platforms on BigQuery, semantic layer migrations to Looker, observability and SIEM on Elasticsearch, and a growing portfolio of internal agentic AI products. Architects at SquareShift are not slide-deck architects. They write reference implementations, pair with engineers, and own technical decisions all the way to production.
We are hiring a Technical Architect to lead the design of our most complex engagements and to set the technical direction for one of our practice areas — Cloud & Data Platforms, AI/ML & Agentic Systems, or Observability & Search.
You will be the senior technical voice on 2–3 concurrent engagements: scoping with clients in pre-sales, owning the architecture from RFC to go-live, and resolving the hard problems that engineers cannot resolve alone. You will also help shape our reusable accelerators (T2L, M2L, P2L, C2L for BI migrations; agent frameworks for Conversational BI and AIResolveX) so that the second engagement of a kind is faster and cleaner than the first.
Architecture & Design
Lead end-to-end architecture for client engagements: data platforms on GCP (BigQuery, Cloud Run, GKE, Dataflow, Pub/Sub), semantic layers in LookML, agent systems on Vertex AI / Google ADK, or Elasticsearch/OpenSearch deployments at scale.
Make the deployment-platform call — Cloud Run vs GKE vs serverless — based on workload shape, latency, cost, and the client's operational maturity. Document the trade-off, don't default to one.
Write architecture decision records that engineers can build from and clients can defend internally — covering trade-offs, alternatives considered, and operational implications.
Own non-functional requirements: latency targets, cost envelopes, security posture (HIPAA/GDPR/PII handling where relevant), observability, and disaster recovery.
Design for multi-tenancy, scale, and the realities of consulting handover — code that the client team can run after we leave.
Write reference implementations and the hardest 10–20% of code on each engagement — the pieces that unblock the rest of the team.
Run spikes and POCs to de-risk new patterns before they hit a delivery plan.
Pair with senior engineers on debugging, performance tuning, and production go-lives.
Partner with Pre-Sales on scoping calls, technical workshops, and SOW reviews. You are the engineer in the room when a prospect's CTO is asking hard questions.
Build and maintain reusable accelerators, reference architectures, and migration playbooks within your practice area.
Represent SquareShift externally — partner technical reviews with Google Cloud and Elastic, blog posts, conference talks, and the occasional joint webinar.
10+ years in software/data engineering, with at least 3 years in an architect, principal, or staff-level role owning systems end-to-end.
Deep, current expertise in at least one of our practice areas:
Cloud & Data — BigQuery at scale, Looker/LookML modelling, GCP services (Cloud Run, GKE/Kubernetes, Dataflow, Pub/Sub, Vertex AI), Helm and container deployment patterns, and modern data stack tooling (dbt, Airflow).
AI/ML & Agentic Systems — production LLM applications, RAG architectures, agent orchestration (ADK, LangGraph, MCP), evaluation frameworks, and cost/latency engineering for LLM workloads.
Observability & Search — Elasticsearch/OpenSearch cluster design, ingest pipelines, SIEM/security analytics, and capacity planning at multi-TB ingestion scales.
Production track record. You can point to systems running today, with traffic, that you designed and helped build.
Strong design communication. Your RFCs and diagrams are clear enough that a senior client architect can disagree with you on substance, not on what you meant.
Pragmatism. You optimise for the outcome — not the most novel framework. You know when boring infrastructure is the right answer.
Hands-on experience with Anthropic Claude, Google ADK, OpenRouter, or similar agent platforms in production.
Background in BI migrations to Looker from Tableau, MicroStrategy, Cognos, or Power BI.
Elastic certifications, Google Cloud Professional certifications, or open-source contributions in our ecosystem.
Prior experience in a consulting or partner-led delivery model — you understand the rhythm of pre-sales, SOW, delivery, and handover.
Architecture with teeth. Our architects ship code, not just decks. If you have been quietly frustrated by architect roles that drift from production, this is a course correction.
Variety with depth. Multiple engagements per year across genuinely different problem spaces — without the chaos of a body-shop model.
Direct partner access. Real working relationships with Google Cloud and Elastic engineering teams; you will ship things that show up in case studies and partner reviews.
Influence on the AI roadmap. Our agentic product portfolio (Conversational BI, AIResolveX, Agentic QA) is being designed now. Architects here help decide where it goes.
