Equinix Hiring Fresher AI Engineer + Python Full Stack @ Bangalore Location
Equinix Hiring Fresher Staff Python Full Stack AI Engineer @ Bangalore Location
Job Summary
We are seeking a Full Stack Engineer to design and build agentic AI workflows on Google Cloud Platform (GCP). This role will focus on developing intelligent, orchestrated systems that can reason, take action, interact with enterprise platforms, and support complex business processes through AI-driven automation.
APPLYNOW!
The ideal candidate combines strong software engineering fundamentals with hands-on experience in cloud-native development, APIs, distributed systems, and modern AI application patterns. You should be comfortable building beyond simple chat experiences and into robust workflow-driven solutions that integrate with enterprise systems, tools, and data platforms.
This is an opportunity to help shape the next generation of AI-enabled experiences by building scalable, secure, and maintainable services in a production enterprise environment.
Responsibilities
Design, build, and maintain agentic AI workflows that can plan, reason, retrieve information, invoke tools, and complete multi-step tasks
Develop cloud-native services and orchestration components on Google Cloud Platform, using services such as Vertex AI, Cloud Run, GKE, Pub/Sub, Cloud Functions, and related GCP capabilities
Build integrations with enterprise systems, APIs, databases, event streams, and external services to enable end-to-end AI-driven business workflows
Engineer reliable application layers for prompt orchestration, tool execution, context handling, memory patterns, retrieval, and workflow state management
Collaborate with architects, product managers, and domain experts to translate business problems into scalable technical solutions
Help define patterns and standards for AI workflow design, observability, testing, security, and operational support
Optimize solutions for performance, resilience, cost, and maintainability
Implement strong engineering practices, including CI/CD, automated testing, code reviews, monitoring, and infrastructure-as-code
Partner with security and platform teams to ensure compliant and secure handling of data, models, and enterprise integrations
Contribute to the evaluation and adoption of emerging frameworks, tools, and patterns relevant to AI agents and workflow orchestration
Qualifications
Bachelor’s degree in Computer Science, Software Engineering, or a related technical field, or equivalent practical experience
Proven experience as a software engineer building production-grade applications and services
Strong programming skills in one or more modern languages such as Python, TypeScript, or Java
Experience building solutions on Google Cloud Platform
Experience developing and consuming REST APIs, event-driven architectures, and distributed systems
Strong understanding of software design, testing, debugging, and operational support in cloud environments
Experience working with data stores, including relational databases, NoSQL databases, vector stores, and analytical platforms
Familiarity with containerization and deployment technologies such as Docker and Kubernetes
Ability to work across technical and functional teams in a fast-moving environment
Preferred Experience
Experience building AI-native applications, including LLM-based workflows, retrieval-augmented generation, tool use, or multi-step orchestration patterns
Hands-on experience with Vertex AI, foundation models, prompt engineering, evaluation methods, and model integration patterns
Experience with agent orchestration frameworks or workflow platforms used to coordinate AI-driven tasks
Familiarity with enterprise integration patterns, middleware, event streaming, and service orchestration
Experience designing systems with observability, traceability, and human-in-the-loop controls
Understanding of AI application risks, including hallucination, security boundaries, governance, and responsible AI controls
Experience in enterprise environments where reliability, compliance, and scalability are critical
What Success Looks Like
You build AI workflow services that are not just experimental, but production-ready
You create systems that can reliably connect reasoning, data, and action across enterprise platforms
You help establish sound engineering patterns for agentic AI development in GCP
You balance innovation with discipline, building solutions that are secure, scalable, and maintainable
Example Areas of Work
Multi-step AI agents that gather context, call tools, and complete business tasks
Workflow orchestration for approvals, case management, knowledge retrieval, and employee support experiences
Integrations between AI services and enterprise systems such as HR, IT, collaboration, and knowledge platforms
Observability and control layers for AI decisioning, tool invocation, and workflow outcomes
