Solutions Architect

Solution Architect - (Google Cloud, Agentic GenAI, MCP)

Role summary

People Tech Group is seeking a hands-on Solution Architect to design and lead an

industrial Integrity Operating Window (IOW) AI platform for a leading refinery. You will own

the end-to-end architecture across GCP data services, event / middleware, agentic GenAI

(MCP microservices per source), and the AI & knowledge base layer (RAG over standards

like API 571 / 584 and SOPs) - delivering a secure, real-time, expert-in-the-loop system

Location : India (preferred IST timezone)

Function : Engineering / Architecture

Type : Full-time

Responsibilities : -

 Own the reference architecture : Translate business & SME needs into a cloudnative,

real-time architecture spanning on-prem connectors

(PI / IOW / LIMS / APM / ERP / Logbook) → MCP adapter layer → event bus → agentic AI →

dashboard & workflows

 Design MCP layer (per-source microservices) : Define APIs, schemas, and contracts

for MCP-PI, MCP-IOW / LIMS, MCP-APM, MCP-ERP, MCP-Logbook; standardize ondemand

aggregates (24h / 7d / 30d / 90d), normalized events, retries, and backpressure

 Evented core : Architect and tune Pub / Sub (or Kafka) topics for

deviations / alarms / actions; ensure idempotency, ordered processing where

required, and replay strategy

 AI & knowledge base : Lead agentic GenAI design—Data Analysis Agent (tool use

over MCPs), Knowledge Agent (RAG over standards like API 571 / 584, vendor

manuals, SOPs), Expert-Feedback Agent (thumbs / annotations loop), Orchestrator

(GPT-class LLM)

 RAG & vector search : Choose and implement vector store (Cloud SQL + pgvector,

Vertex AI Matching Engine, or Milvus); define chunking, embeddings, refresh

cadence, grounding / citations

 Security & governance by design : Enforce VPC / VPN / Interconnect, IAM (least

privilege / service accounts), Cloud KMS (CMEK), Cloud Audit Logs, Data Catalog &

Lineage, DLP & data quality rules, SSO / OIDC

 Data services & middleware : Select and size Cloud Run / GKE for MCPs & BFF, Cloud

Storage for docs / dumps, Memorystore for feature cache, optional BigQuery

(analytical store) without coupling runtime

 Integration workflows : Orchestrate Action Tracker ↔ ERP (SAP PM / Oracle EAM) via

MCP-ERP; define SLAs, ownership, and auditability for IOW→RBI hand-os (GE APM)

 Observability & SLOs : Establish metrics, traces, logs, and SLOs (latency, freshness,

accuracy), plus runbooks for incident response

 Cost & scale : Model infra + LLM cost envelopes, implement autoscaling,

request / response token budgets, and caching strategies

 Delivery leadership : Produce architecture docs, ADRs, sequence diagrams; guide

developers, data / ML engineers, and MLOps; engage SMEs (operations,

corrosion / RBI) for iterative validation

Required qualifications

 10+ years in distributed systems / data / AI architecture with at least 3+ years on GCP

leading production solutions

 Proven design of event-driven architectures with Google Pub / Sub (or Kafka), and

microservices on Cloud Run or GKE

 Strong with GCP data stack : Cloud Storage, Cloud SQL / Postgres (pgvector),

Dataflow / Data Fusion (or equivalent ETL), Cloud Monitoring, Cloud Logging, Secret

Manager, IAM, KMS, VPC

 Hands-on GenAI + RAG : embeddings, vector search, grounding / citations, prompt

tooling, and safety / guardrails; experience integrating OpenAI / Vertex AI (Gemini) or

Anthropic models

 MCP-style adapter design : built source-specific microservices / APIs that normalize

schemas, perform windowed aggregates, and publish events

 Integration exposure to OSIsoft PI / PI Web API, IOW / LIMS, GE APM (RBI), and

SAP / Oracle ERP (REST, OData, queues, or middleware)

 Practical security & compliance : IAM design, network segmentation, CMEK,

auditability, lineage; understands safety-critical environments

 Excellent stakeholder skills : can translate SME input (e.g. API 571 / 584, IOW

practices) into technical decisions

Nice-to-have (preferred)

 LLMOps / MLOps : Vertex Pipelines, model registries, prompt / versioning, evals, AB

tests, telemetry

 Action management integrations (SAP PM / Maximo), Apigee / API gateway exposure

 Time-series modeling (feature engineering, basic LSTM / TFT / Prophet, or XGBoost

classifiers for risk scoring)

 Graph / causal modeling for chain-link analysis (propagation across units)

 Experience hardening BFF / API layers, RBAC in UI, and expert-feedback / annotation

UX

 Oil and Gas Industrial domain : Refining, IOW (knowledge on standards like API RP

571 / 584), corrosion loops, RBI workflows