Resolve Tech Solutions (RTS) & Juno Labs :

Leading the AI Revolution. Juno Labs is at the forefront of AI and ML innovation. We are a global technology services company with a mission to modernize and transform industries that matter by providing world-class IT services, consulting, and implementation solutions. We are the preferred IT partner for both Fortune 500 enterprises and small and medium businesses across the diverse verticals of telecom, retail, government, aerospace, defence, and real estate.

Job Location : Bangalore, Prestige Tech Park, Kaadubeesanahalli.

Work mode : Hybrid (3 days from office / 2 days WFH).

IMPORTANT NOTE : We only require candidates from Bangalore location.

Experience : 5 to 10+ years.

Role Overview :

We are looking for an experienced Full Stack Engineer with strong hands-on expertise in React, Python, and MLOps to build and operate modern enterprise applications. The role requires end-to-end engineering ownership across user interfaces, APIs, microservices, data, AI-enabled workflows, testing, cloud deployment, observability, and production support. The ideal candidate combines strong application-development fundamentals with practical cloud and MLOps experience and can collaborate effectively with product, architecture, QA, DevOps, and business teams.

Key Responsibilities :

- Own full-stack features from technical design and development through integration, testing, deployment, monitoring, and production support.

- Work with product owners, architects, business stakeholders, QA, and DevOps teams to clarify requirements, workflows, constraints, and technical trade-offs.

- Design and build responsive web applications using React / Next.js and scalable backend services using Python, FastAPI, Flask, Node.js, or Golang.

- Design secure REST APIs, microservices, Kafka-based event-driven workflows, and resilient enterprise integration patterns.

- Build and operationalize AI-enabled capabilities using LLMs, RAG, MCP, agentic workflows, prompt engineering, evaluation, guardrails, and MLOps practices.

- Optimize frontend, API, database, caching, and distributed-system performance through profiling, load testing, tuning, and scalability improvements.

- Automate quality using unit, integration, API, UI, regression, and performance testing, with Playwright for end-to-end automation.

- Deploy and operate containerized applications using Docker, Kubernetes, Terraform, Terragrunt, CI/CD, and AWS, Azure, or GCP.

- Implement observability and enterprise integrations using ServiceNow, Datadog, OpenTelemetry, Splunk, LogicMonitor, CloudWatch, and similar platforms.

- Troubleshoot production issues using logs, metrics, traces, and root-cause analysis; implement durable corrective and preventive actions.

- Create technical documentation, architecture views, runbooks, deployment guides, and reusable engineering patterns; mentor team members where required.

Required Technical Skills :

- Full-Stack Engineering : React, Next.js, TypeScript/JavaScript; Python, FastAPI, Flask, Node.js, or Golang. Strong ownership across frontend, backend, API integration, and reusable application design.

- APIs, Microservices & Kafka : REST APIs, microservices, distributed systems, authentication, resiliency, retries, idempotency, Kafka-based event-driven architecture, and enterprise integrations.

- AI, LLM & MLOps : LLMs, RAG, MCP, agentic AI, prompt engineering, embeddings, vector search, evaluation, guardrails, model/application deployment, monitoring, and cost controls.

- Data, SQL/NoSQL & Redis : PostgreSQL, Oracle, MongoDB, DynamoDB, SQL/NoSQL, Redis, data modeling, indexing, query tuning, transactions, and caching patterns.

- Performance Engineering : Frontend and backend profiling, load testing, concurrency, latency reduction, API/database tuning, caching, scalability, reliability, and cloud cost optimization.

- QA & Test Automation : Unit, integration, API, UI, regression, and performance testing; Playwright as a core end-to-end automation skill.

- Cloud, DevOps & IaC : AWS/Azure/GCP, Docker, Kubernetes, Terraform, Terragrunt, CI/CD, IAM, secrets, networking, environment promotion, deployment, rollback, and production operations.

- Observability & Integrations : ServiceNow, Datadog, OpenTelemetry, Splunk, LogicMonitor, CloudWatch; logs, metrics, traces, dashboards, alerting, health checks, and incident diagnostics.

- Production & Security : Strong debugging, production support, root-cause analysis, secure coding, OWASP, API security, encryption, least privilege, and operational readiness.

Experience & Qualifications :

- 5 to 10+ years of professional software engineering experience, with strong hands-on delivery across frontend, backend, cloud, and production environments.

- Experience in full-stack product engineering, platform engineering, enterprise application development, implementation, or solution delivery is highly valuable.

- Ability to convert business requirements into practical technical designs, incremental releases, and reliable production solutions.

- Experience working in Agile teams across product, QA, DevOps, security, architecture, and business stakeholders.

- Bachelors degree in Computer Science, Engineering, Information Technology, or equivalent practical experience.

Core Behaviors & Soft Skills :

- Excellent verbal and written communication with the ability to explain complex technical topics to business and technical stakeholders.

- Strong ownership, product thinking, engineering discipline, and accountability for outcomesnot only assigned tasks.

- Comfortable working in fast-moving environments with a bias for action, structured problem-solving, and continuous learning.

- Collaborative, low-ego team player who communicates risks early and remains calm during production incidents.

Preferred / Nice-to-Have :

- Experience moving AI-enabled or data-intensive applications into secure production services; exposure to vector databases, LLM evaluation, AI security, SRE, high-availability design, mentoring, and relevant cloud or Kubernetes certifications is a plus.