Technical Architect (Backend)

Symphony Industrial AI, Inc.

India

Hybrid

INR 4,000,000 - 7,000,000

Full time

7 days ago
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Benefits offered by this job

Hybrid working model
Professional growth opportunities
Access to latest technologies

Job summary

Symphony Industrial AI, Inc. is seeking a seasoned software architect and hands-on engineer to design and build scalable Python-based systems on our Iris Smart Manufacturing platform. The role blends architecture with coding, data, and cloud operations in a hybrid work setting.

You will lead by example, mentor engineers, and collaborate across frontend, data, and platform teams to deliver robust, observable, and high-performance solutions for manufacturing sectors.

Qualifications

  • Strong hands-on Python experience including design, debugging, and performance tuning.
  • Experience building and scaling microservices-based distributed systems.
  • Deep understanding of concurrency, async processing, and event-driven architectures.
  • Solid API design experience (REST and gRPC).
  • Experience with cloud platforms and container orchestration.

Responsibilities

  • Design scalable, fault-tolerant distributed systems using microservices.
  • Contribute high-quality Python code and lead by example.
  • Drive performance optimization, load testing, and RCA.
  • Mentor engineers and raise the engineering bar.
  • Collaborate with frontend, data, and platform teams.

Skills

Python
Microservices architecture
Concurrency & async
REST & gRPC APIs
Cloud platforms
Kubernetes
Docker
CI/CD pipelines
Observability
GenAI tools

Tools

Kubernetes
Docker
CI/CD
Prometheus
Grafana
Kafka
Airflow
Azure
PostgreSQL
MongoDB

Job description

Introduction
Overview

Our solutions, hosted on our Iris Smart Manufacturing platform, combine equipment and process domain expertise in Mining & Metals, Oil & Gas, Chemicals & Petrochemicals with the state-of-the-art in data sciences, machine learning, and process optimization. The IRIS platform can work in hybrid mode and is built using a microservices architecture. The applications are containerised and run on Azure Kubernetes Service and use Azure blob storage, Data Lake, IoT Hub, Event Hub, Event Grid, and Queues.

What Success Looks Like
  • Ability to take ambiguous problem statements and convert them into clear, executable technical plans
  • Consistent delivery of high-quality, production-grade systems with strong reliability and performance
  • Demonstrated impact in eliminating bottlenecks, improving system efficiency, and scaling platforms
  • Strong influence across teams through clear technical communication and leadership
Job Description
Responsibilities
Architecture & System Design
  • Design scalable, fault-tolerant distributed systems using microservices architecture
  • Ensure systems are built with observability, resiliency, and extensibility by design
Hands-on Development (Python-first)
  • Actively contribute to core codebases with high-quality, maintainable Python code
  • Lead by example in coding standards, debugging, and performance optimization
  • Build reusable frameworks, libraries, and internal platforms
Problem Solving & Performance Engineering
  • Identify and resolve system bottlenecks (CPU, memory, I/O, network, DB)
  • Drive performance tuning, load testing, and scalability improvements
  • Establish benchmarks and SLO-driven engineering practices
  • Lead root cause analysis (RCA) and implement long-term fixes
  • Design guardrails to prevent 99% of known failure modes
  • Improve observability (metrics, logs, traces) across systems
Technical Leadership & Mentorship
  • Lead a team of senior, mid-level, and junior engineers
  • Mentor engineers in system design, coding best practices
  • Raise the overall engineering bar across teams
Cross-Team Collaboration
  • Work effectively with frontend, backend, data, and platform teams
  • Ensure features are implemented end-to-end in a cohesive and scalable manner
  • Communicate technical concepts clearly to both engineers and leadership
Required Skills & Qualifications
  • Strong hands-on experience in Python (design, debugging, performance tuning)
  • Experience building and scaling microservices-based distributed systems
  • Deep understanding of concurrency, parallelism, async processing, and eventdriven architectures
  • Strong grasp of API design (REST/gRPC)
  • Experience with data systems: SQL (Postgres) and NoSQL (MongoDB, Elasticsearch), Messaging systems (Kafka, Event Hubs, queues), data-intensive systems and pipelines
  • Hands-on experience with cloud and infrastructure: AWS / Azure / GCP, Docker, Kubernetes, CI/CD pipelines
  • Familiarity with observability tools: Prometheus, Grafana, Kibana (or similar)
  • Experience with workflow orchestration tools (Airflow, NiFi or equivalent)
  • Exposure to Data / AI platforms (preferred)
  • Strong focus on code quality, testing, and automation
  • Comfortable using GenAI development tools (e.g., Cursor, Copilot) to improve productivity
  • Experience in working with Ontology/Knowledge Graph in any complex data ecosystem is a huge plus
Compensation & Benefits
  • Competitive salary and benefits package
  • Flexible hybrid working model
  • Opportunities for professional growth and development
  • Collaborative and inclusive work environment
  • Access to the latest technologies and tools
  • Opportunity to make a tangible impact on cutting-edge Retail/CPG AI solutions
Hybrid/On-site Requirements
  • Flexible hybrid working model
Diversity & Inclusion Statement

We are committed to building a diverse and inclusive team and encourage candidates from all backgrounds to apply.

About Us

SymphonyAI is building the leading enterprise AI SaaS company for digital transformation across the most critical and resilient growth industries, including retail, consumer packaged goods, financial crime prevention, manufacturing, media, and IT service management. Since its founding in 2017, SymphonyAI today serves 1500+ Enterprise customers globally and has grown to 3,000 talented leaders, data scientists, and other professionals across over 30 countries.

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