Introduction




Job Title: Technical Architect




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.



We are looking for a Technical Architect who combines deep Python expertise, strong computer science fundamentals, and hands-on engineering rigor to design and build scalable, high-performance systems. This is a high-ownership, high-impact role where the individual is expected to operate using first-principles thinking, be deeply hands-on with code, solve ambiguous, complex technical problems, and drive end-to-end architecture and execution. The architect will work closely with Engineering Managers, Directors, Product Managers, and cross-functional teams to translate high-level product goals into robust, scalable, and production-ready systems.




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.