Software Engineer II (Golang)

Team: Product Development

Location: Bangalore, Hyderabad

Commitment: Full-time

Workplace Type: onsite

Job Responsibilities:

AI-Powered POS, EPS & Forecourt Development: Build intelligent systems across Point of Sale, Electronic Payment Systems, and Forecourt management using Go, incorporating real-time analytics, payment integration, inventory intelligence, and multi-step automation workflows for retail, hospitality, and fuel environments.

Product Innovation & AI Integration: Develop next generation Go microservices with generative AI features including predictive pump management, fraud detection, and forecourt monitoring optimized for performance, UX, and safety compliance.

Intelligent System Architecture: Leverage LLMs and multimodal models within Go service architectures using gorilla/mux for stateful context management, delivering context-aware experiences across EPS, FEP, and forecourt domains.

Payment & Forecourt Integration: Develop and maintain integrations with payment terminals (ISO 8583, EMV, NFC) and forecourt controllers (Gilbarco, Wayne) using IFSF, OPT, and serial/TCP protocols, ensuring end-to-end PCI-DSS, compliance and reliable pump authorization workflows.

Backend API & Cloud Deployment: Design RESTful and event-driven APIs using Go's standard HTTP stack and gorilla/mux; deploy and maintain Go microservices on Kubernetes using Docker multi-stage builds, Helm charts, Jenkins CI/CD pipelines, and MongoDB-backed observability tooling for high-availability transactional workloads.

 Testing, UI & Cross-Functional Collaboration: Write automated tests using Go's native testing package and testify; contribute to agent evaluation frameworks; instrument services with structured logging (lumberjack) and distributed tracing; work closely with product, operations, and POS teams to translate payment workflows into production-ready solutions.

Job Requirements:

Core Experience: 3–5 years of professional software engineering with demonstrated ownership in production systems; experience in transactional, high-availability, retail, payment, or forecourt environments is a strong plus.

Go Stack: Strong proficiency in Go (1.20+), including gorilla/mux, MongoDB driver, JWT/OAuth 2.0, goroutines and channel-based concurrency, interface-driven design, and Go module management.

 Payment & Forecourt Protocols: Familiarity with ISO 8583, EMV, NFC, and PCI-DSS compliance; familiarity with forecourt integration (IFSF, OPT, pump authorization) and serial/TCP communication protocols is recommended.

Agentic Systems Mastery: Proven hands-on experience building intelligent, automation-driven systems any platform, including agent-based workflow orchestration for multi-step transactions.

AI & Backend Integration: Hands-on experience integrating LLMs or AI services into backend systems, including prompt engineering, RAG, and automation workflows

 Data & Vector Technologies: Familiarity with vector databases, embeddings, recommendation systems, and data pipelines for customer behavior analytics and product intelligence

Cloud & DevOps: Experience deploying Go applications to AWS with Docker multi-stage builds, Kubernetes Stateful Sets /Deployments, Helm chart management, and Jenkins CI/CD pipelines.

 Web APIs & Real-Time Communication: Experience designing distributed microservice architectures with OAuth 2.0 M2M authentication, RESTful API design, inter-service coordination patterns, and event-driven processing for live transaction and forecourt operations.

 Testing & Security: Strong test-driven development practices using Go's native testing package and testify; solid understanding of secure coding, PCI-DSS, precise currency arithmetic and protection against injection/tampering in high-value payment transactions.

Soft Skills: Strong communication and collaboration ability; growth mindset; effective cross-domain teamwork with initiative-taking and good judgment about when to seek guidance.

Candidates must demonstrate the ability to effectively leverage AI tools, automation, and modern AI technologies to enhance productivity, problem-solving, and innovation in their daily work. Proven ability to use AI-powered tools to improve efficiency, accelerate development, and solve complex problems. AI proficiency is required: ability to use and adapt to modern AI tools and technologies as part of day-to-day work.

Behavioral Competencies:

Cultivates Innovation
Decision Quality
Manages Complexity
Drives Results
Business Insight