Technical Architect

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.

• 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.