Full stack Developer

Click "Apply Now" in https://gosuperedtech.com/career/ai-system-engineer to apply

Role Overview

We are looking for a Junior AI System Engineer who is eager to build a career in AI systems, automation, backend workflows, cloud infrastructure, and intelligent product operations.

This role offers an opportunity to work closely with experienced engineers, product teams, and AI specialists on real AI-powered systems that support learners, educators, schools, and internal business operations.

At GoSuper EdTech, our cloud infrastructure is built on Google Cloud Platform — GCP. You will get hands-on exposure to GCP-based systems, backend services, AI integrations, deployment workflows, monitoring, cloud storage, databases, and automation pipelines.

You will help design, integrate, test, monitor, and maintain AI-enabled systems using modern tools such as AI APIs, LLMs, automation workflows, backend services, databases, GCP services, cloud deployment tools, and monitoring systems.

This role is ideal if you are curious about AI, comfortable with technical problem-solving, and interested in building reliable systems that connect software, data, cloud infrastructure, automation, and intelligent workflows.

What You’ll Do

• Support the development and maintenance of AI-powered systems, tools, and workflows.
• Assist in integrating AI APIs, LLM platforms, automation tools, and backend services into GoSuper products.
• Work with OpenAI, Gemini, Claude, or similar AI platforms under the guidance of senior engineers.
• Support AI and backend workflows deployed on Google Cloud Platform — GCP.
• Assist with GCP-based services such as Cloud Run, Compute Engine, Cloud Functions, Cloud Storage, Firebase, Firestore, Cloud SQL, BigQuery, Pub/Sub, Cloud Logging, and Cloud Monitoring, based on project needs.
• Help build AI workflows for content generation, chatbot systems, smart recommendations, internal automation, and productivity tools.
• Support backend integrations using Node.js, Python, REST APIs, webhooks, and third-party services.
• Assist in designing and maintaining system workflows that connect databases, applications, AI models, cloud services, and business tools.
• Work with databases such as PostgreSQL, MongoDB, Firebase, Firestore, Supabase, or similar platforms.
• Help test AI outputs, validate workflows, debug issues, and improve system reliability.
• Monitor system performance, API usage, errors, logs, workflow failures, and cloud service health.
• Support deployment, configuration, and maintenance of AI-enabled product features on GCP.
• Collaborate with product managers, developers, designers, QA teams, and business teams to understand requirements and deliver working solutions.
• Participate in daily standups, sprint planning, technical discussions, and team meetings.
• Document AI workflows, system logic, API integrations, prompts, GCP configurations, deployment steps, and troubleshooting processes.
• Continuously learn and apply best practices in AI systems, backend engineering, automation, GCP cloud infrastructure, and production support.

What We’re Looking For

• 6 months to 1 year of experience in AI systems, backend development, software engineering, automation, DevOps support, cloud support, system integration, or relevant internship/project experience.
• Basic understanding of AI tools, LLMs, APIs, automation workflows, and software systems.
• Working knowledge of JavaScript, TypeScript, or Python.
• Basic backend development experience with Node.js, Express, NestJS, FastAPI, or similar frameworks.
• Basic understanding of Google Cloud Platform — GCP or willingness to learn GCP-based deployment and monitoring workflows.
• Understanding of REST APIs, webhooks, third-party integrations, and data flow between systems.
• Interest in AI APIs, prompt workflows, chatbot systems, automation tools, and intelligent product features.
• Basic understanding of databases such as PostgreSQL, MongoDB, Firebase, Firestore, Supabase, or Redis.
• Ability to debug technical issues across APIs, workflows, logs, backend services, and cloud deployments.
• Good analytical thinking and problem-solving ability.
• Ability to write clear documentation for workflows, integrations, cloud configurations, and technical processes.
• Eagerness to learn new tools, AI platforms, system design concepts, GCP services, and cloud technologies.
• Good communication skills to work with technical and non-technical teams.
• Ownership mindset and willingness to take responsibility for assigned tasks.
• Comfortable working in a fast-paced startup environment.

Nice to Have

• Familiarity with AI APIs such as OpenAI, Gemini, Claude, or similar platforms.
• Basic understanding of prompt engineering and LLM-based workflows.
• Exposure to LangChain, LlamaIndex, embeddings, vector databases, or retrieval-augmented generation.
• Basic experience with GCP services such as Cloud Run, Cloud Functions, Firebase, Firestore, Cloud Storage, Cloud SQL, BigQuery, Pub/Sub, Cloud Logging, or Cloud Monitoring.
• Exposure to Google AI tools, Vertex AI, Gemini API, or AI-related services on GCP.
• Experience with automation tools, workflow builders, webhooks, or integration platforms.
• Exposure to Docker, CI/CD pipelines, GitHub Actions, deployment workflows, or cloud-based release processes.
• Experience working with logs, monitoring tools, API testing tools, or debugging platforms.
• Familiarity with Postman, Git, GitHub, Notion, Zoho, Slack, or similar productivity tools.
• Experience building chatbots, AI assistants, internal tools, or automated workflows.
• Personal, academic, internship, or open-source projects related to AI, automation, backend systems, GCP, or cloud tools.
• Interest in SaaS, EdTech, AI-powered products, and startup environments.

What You’ll Gain

• Hands-on experience building AI-powered systems in a real startup environment.
• Practical exposure to AI APIs, LLM workflows, automation systems, backend services, and GCP cloud infrastructure.
• Mentorship from senior engineers and product leaders.
• Experience working across AI, backend engineering, databases, APIs, integrations, deployment, system monitoring, and cloud operations.
• Opportunity to contribute to real product features used by learners, educators, schools, and institutions.
• Exposure to SaaS product development, EdTech workflows, AI-driven business solutions, and GCP-based production systems.
• Learning culture that encourages experimentation, feedback, and continuous improvement.
• Opportunity to understand how AI systems are designed, deployed, monitored, scaled, and improved in production.
• Access to Cult Elite and Cult Play Pass, offering wellness and lifestyle benefits to keep you energized and inspired.

Compensation

• Competitive salary with performance-based bonuses.
• Equity ownership through ESOPs — own a piece of the company you help build.
• Flexible remote work options with occasional Bengaluru office meetups.
• Health and wellness perks, including Cult Elite membership and Cult Play Pass for employees.
• Learning and development support to help you grow in AI systems, backend engineering, automation, SaaS, and GCP cloud technologies.
• Team retreats, virtual hangouts, and a collaborative work culture.

We are looking for a AI System Engineer who is eager to build a career in AI systems, automation, backend workflows, cloud infrastructure, and intelligent product operations. Apply in https://gosuperedtech.com/career/ai-system-engineer

About E2M:

E2M Solutions works as a trusted white-label partner for digital agencies. We support agencies with consistent and reliable delivery through services such as website design, web development, eCommerce, SEO, AI SEO, PPC, AI automation, and content writing .Founded on strong business ethics, we are an equal opportunity organization powered by 300+ experienced professionals, partnering with 400+ digital agencies across the US, UK, Canada, Europe, and Australia. At E2M, we value ownership, consistency, and people who are committed to doing meaningful work and growing together .If you’re someone who dreams big and has the gumption to make them come true, E2M has a place for you.

Role Overview:

We are seeking a highly skilled and client-centric AI Consultant/AI Adoption Specialist to join our growing team. In this pivotal role, you'll serve as a vital link between our clients' strategic objectives and the transformative power of AI. You'll primarily focus on understanding their needs, scoping opportunities, and architecting actionable AI roadmaps.

Key Responsibilities:

• Collaborate closely with clients to understand their challenges and identify opportunities to apply AI.
• Assess client requirements and prepare solution strategies using AI tools and methodologies.
• Work with internal teams to design, propose, and help execute AI-powered solutions.
• Provide AI-based recommendations that align with the client’s business objectives.
• Communicate technical possibilities in a business-friendly manner to decision-makers.
• Take ownership of the client journey from discovery to implementation and support.
• Stay updated with AI trends, tools, and real-world use cases that can benefit clients.

Required Skills & Qualifications:

• Minimum 2+ Years of hands on experience into Custom AI Development.
• Minimum 3+ years of experience in roles like Project Manager, Customer Success Manager, or Account Manager, preferably in a service-based company or digital agency.
• Strong understanding of AI concepts, trends, and tools (e.g., NLP, ML, Chatbots, Automation, native cloud technologies).
•  Some hands-on experience in AI projects – either through execution, coordination, or implementation.
• Ability to manage multiple client engagements and communicate effectively with both technical and non-technical stakeholders.
•  Strong problem-solving mind set with the ability to translate business needs into AI opportunities.
• Flexible to work with international clients, especially in the US time zone as needed.

EMBEDDED AI ENGINEERING POD

AI Implementation Engineer Role

Level: AI Implementation Engineer Senior / Advanced - 6+ years

Practice: Wissen GenAI

Locations: Mumbai / Bengaluru / New York - hybrid, embedded with delivery teams

Reports to: EMBEDDED AI PRACTICE Senior AI Engineering Specialist (Architect); Wissen GenAI Program Lead

Embedded inside enterprise delivery teams, you work closely with global, cross-regional teams to turn prioritized GenAI use cases into production software - building, integrating, and hardening Azure-based AI solutions and accelerating adoption within the teams you join.

You deliver production software and help the teams you join work faster.

As an embedded AI Implementation Engineer, you help convert prioritized use cases into shipped, governed, measurable software.

Key responsibilities

1. Build and ship.

Implement GenAI features end to end on Azure - RAG pipelines, agents, APIs, and UI integrations - against enterprise systems and data.

2. Embed and enable.

Work inside the delivery pods: pair with their engineers, remove blockers, and transfer GenAI skills so adoption sticks after you move on.

3. Productionize.

Add evaluation, observability, guardrails, caching, and CI/CD so prototypes become reliable, cost-efficient services.

4. Integrate securely.

Connect to enterprise data with correct access control, secrets management, and compliance with enterprise security standards and handling of sensitive data.

5. Iterate on quality.

Use evaluation results and user feedback to improve grounding, accuracy, latency, and cost.

6. Measure.

Track delivery and quality metrics that roll up to the program's targets.

Must-have qualifications

• 6+ years in software engineering, with 2+ years building GenAI/LLM applications in production.
• Strong Python (incl. async) and Java (the primary enterprise application stack; Spring a plus); solid API and systems design.
• Azure GenAI hands-on: Azure OpenAI, Azure AI Foundry, Azure AI Search for RAG, Azure AI Document Intelligence (IDP), and Prompt Flow.
• Agent frameworks: Microsoft Agent Framework / Semantic Kernel / AutoGen (or LangChain / LangGraph) and tool / function calling.

Preferred

• RAG fundamentals: embeddings, chunking, vector search, reranking, and grounding.
• Data platforms: Snowflake including Cortex AI (Cortex Search, LLM functions) and SQL, for accessing and grounding on enterprise data.
• Prompt engineering as versioned code; building and running evaluations.
• DevOps: Azure DevOps / GitHub Actions, Docker, AKS / Azure Functions, and observability.
• Financial services or other regulated environments.
• Front-end (React) for AI-assisted UX; streaming and token level operations.
• Azure AI Content Safety and responsible-AI practices.
• Certification: Azure AI Engineer Associate.

What success looks like - first 6 to 12 months

• Multiple GenAI features shipped to production within the embedded delivery pods.
• Measurable adoption and productivity uplift in the teams you support.
• Reusable components adopted from the architects' reference framework.
• Clear contribution to faster time-to-market and lower defect rates.

* Strong practical knowledge and interest in modern AI tools.

* Genuine curiosity and willingness to continuously learn.

* Ability to research, experiment, implement, troubleshoot and improve independently.

* Good understanding of prompting and AI workflows.

* Strong problem-solving mindset.

* Basic understanding of APIs, integrations and automation.

* Ability to explain technology clearly to non-technical people.

* Comfortable using AI to solve real-world business problems.

About the Job :

We are looking for a passionate and driven AI Intern to join our dynamic team. As an intern, you will have the opportunity to work on real-world projects, develop AI models, and collaborate with experienced professionals in the field. This internship is designed to provide hands-on experience in AI and machine learning, offering you the chance to contribute to impactful projects while enhancing your skills.

Job Description:

We are seeking a talented Artificial Intelligence Specialist to join our dynamic team. As an AI Specialist, you will be responsible for developing, implementing, and optimizing AI models and algorithms. You will collaborate closely with cross-functional teams to integrate AI capabilities into our products and services. The ideal candidate should have a strong background in machine learning, deep learning, and natural language processing, with a passion for applying AI to real-world problems.

Responsibilities:

• Design, develop, and deploy AI models and algorithms.
• Conduct data analysis and pre-processing to prepare data for modeling.
• Implement and optimize machine learning algorithms.
• Collaborate with software engineers to integrate AI models into production systems.
• Evaluate and improve the performance of existing AI models.
• Stay updated with the latest advancements in AI research and apply them to enhance our products.
• Provide technical guidance and mentorship to junior team members.

Requirements:

• Any Graduate / Bachelor's degree in Computer Science, Engineering, Mathematics, or a related field; Master's degree preferred.
• Proven experience in developing and implementing machine learning models and algorithms.
• Strong programming skills in languages such as Python, R, or Java.

Benefits :

• Internship Certificate
• Letter of Recommendation
• Performance-Based Stipend
• Part-time work from home (2-3 hours per day)
• 5 days a week, fully flexible shift

Principal Software Engineer

Company Summary :

As the recognized global standard for project-based businesses, Deltek delivers software and information solutions to help organizations achieve their purpose. Our market leadership stems from the work of our diverse employees who are united by a passion for learning, growing and making a difference. At Deltek, we take immense pride in creating a balanced, values-driven environment, where every employee feels included and empowered to do their best work. Our employees put our core values into action daily, creating a one-of-a-kind culture that has been recognized globally. Thanks to our incredible team, Deltek has been named one of America's Best Midsize Employers by Forbes, a Best Place to Work by Glassdoor, a Top Workplace by The Washington Post and a Best Place to Work in Asia by World HRD Congress. www.deltek.com

Position Responsibilities :

About the Role 

We are seeking a highly motivated AI Solutions Engineer to join Deltek’s growing AI Center of Excellence team to design, develop, deploy, and optimize internal Artificial Intelligence and Machine Learning solutions that solve complex business challenges. The ideal candidate combines deep expertise in AI, machine learning, Generative AI, Large Language Models (LLMs), SLMs, software engineering, cloud computing, and MLOps/LLMOps to build scalable, production-grade AI applications. 

The AI Solutions Engineer will collaborate with AI data scientists, architects, and engineering teams to deliver innovative AI-driven solutions while ensuring security, scalability, governance, and operational excellence. This role reports to the Senior AI Solutions Architect. 

Key Responsibilities 

AI & Machine Learning Development 

• Design, build, train, evaluate, and deploy machine learning and deep learning models. 
• Develop Generative AI solutions using Large Language Models (LLMs) such as GPT, Claude, Gemini, Llama, and Mistral. 
• Implement Retrieval-Augmented Generation (RAG), prompt engineering, fine-tuning, and AI agent frameworks. 
• Build NLP, recommendation systems, forecasting, predictive analytics, and intelligent automation solutions. 
• Optimize model performance, scalability, latency, and cost. 

Software Engineering & Solution Development 

• Develop production-grade AI applications using Python and modern software engineering practices. 
• Build APIs, microservices, and AI-powered enterprise applications. 
• Integrate AI services with enterprise systems, business applications, and data platforms. 
• Apply coding standards, automated testing, CI/CD, and version control best practices. 

MLOps & AI Operations 

• Design and implement MLOps pipelines for model development, deployment, monitoring, and lifecycle management. 
• Automate model training, validation, testing, and deployment processes. 
• Monitor model performance, data drift, hallucinations, and operational metrics. 
• Support continuous improvement and reliability of AI platforms. 

Cloud & Platform Engineering 

• Develop AI solutions on Azure, AWS, or Google Cloud platforms. 
• Leverage cloud-native AI services, containerization, Kubernetes, and serverless technologies. 
• Build scalable architectures supporting enterprise AI workloads and real-time inference. 

AI Governance & Security 

• Ensure compliance with Responsible AI, security, privacy, and regulatory requirements. 
• Implement model governance, explainability, bias mitigation, and risk management practices. 
• Maintain standards for secure design, deployment, and operation of AI solutions. 

Required Qualifications 

Education 

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related technical field. 

Experience 

• 5+ years of software engineering or machine learning development experience. 
• 2+ years of hands-on experience developing and deploying Agentic AI, Generative AI or AI/ML solutions in production environments. 

Technical Skills 

Programming & Engineering 

• Strong expertise in Python. 
• Experience with Java, ReactJS, JavaScript, or similar programming languages. 
• Solid understanding of algorithms, data structures, APIs, and software design principles. 

Artificial Intelligence & Machine Learning 

• Machine Learning and Deep Learning concepts and frameworks. 
• Model training, evaluation, optimization, and deployment. 

Generative AI 

• Large Language Models (LLMs) & SLMs 
• Prompt Engineering 
• Retrieval-Augmented Generation (RAG) 
• AI Agents and Agentic Workflows 
• Fine-tuning and model customization 
• Vector embeddings and semantic search 

Frameworks & Tools 

• PyTorch, TensorFlow, Scikit-learn 
• LangChain, LlamaIndex, Semantic Kernel, MCP, A2A and Transformers 
• FastAPI, Flask 

Data & Analytics 

• SQL and NoSQL databases 
• Data pipelines, ETL, and data modeling 
• Experience with AWS, Azure and Google 

MLOps & DevOps 

• MLflow, Kubeflow, Azure ML, SageMaker 
• Docker and Kubernetes 
• Git, GitHub, Azure DevOps, Jenkins 
• CI/CD automation and model monitoring 

Cloud Platforms 

• AWS (preferred) 
• AWS Bedrock or Azure OpenAI Service 
• AWS SageMaker 
• Google Vertex AI 

Preferred Qualifications 

• Experience designing enterprise-scale AI platforms and products.  
• Knowledge of multi-agent architectures and autonomous AI systems.  
• Experience with vector databases such as Pinecone, Snowflake Cortex, Pgvector, Weaviate, Chroma, or Azure AI Search.  
• Understanding of AI governance, compliance, and Responsible AI frameworks.  
• Relevant certifications in Azure AI, AWS Machine Learning, or Google Cloud AI.

Job Summary/ Job Opportunity:

This is an excellent opportunity for an ideal candidate with a high level of technical proficiency and meeting the below mentioned criteria -- • Strong experience in Machine Learning, Deep Learning, Generative AI, and Large Language Models (LLMs). • Hands-on experience building and deploying production-grade solutions using Azure OpenAI, OpenAI, LangChain, LangGraph, Semantic Kernel, LlamaIndex, and Agentic AI frameworks. • Strong expertise in Python, API development, microservices, and cloud-native architectures. • Experience designing and implementing RAG solutions, vector databases, embeddings, knowledge retrieval systems, and AI copilots. • Experience with Azure cloud services, MLOps, CI/CD pipelines, monitoring, and model lifecycle management. • Strong understanding of AI governance, responsible AI, security, compliance, and model evaluation frameworks. • Ability to lead technical discussions, provide architectural recommendations, mentor team members, and interact with business stakeholde

Key Objectives and Major Responsibilities:

• Design, develop, and implement scalable AI/ML and Generative AI solutions for enterprise applications. • Lead development of intelligent applications leveraging LLMs, RAG pipelines, AI agents, and document intelligence solutions. • Collaborate with business stakeholders, architects, and product teams to translate business requirements into technical solutions. • Design and optimize data pipelines, vector search solutions, embeddings, and retrieval mechanisms. • Build and maintain REST APIs, microservices, and cloud-native AI applications. • Ensure best practices in coding standards, performance optimization, security, scalability, and maintainability. • Drive AI solution deployment using MLOps practices, CI/CD pipelines, monitoring, and observability frameworks. • Perform code reviews, mentor junior developers, and contribute to capability building within the team

Key Capabilities and Competencies:

Knowledge, Skills, Qualification and Experience

• Degree in B.Tech/M.Tech (Computer Science/IT/Data Science) or related discipline preferred, with 3–4 years of relevant experience in AI/ML, GenAI and total 5-7 years of experience. • Proficiency in Python and hands-on experience with ML libraries (scikit-learn, TensorFlow, PyTorch) and GenAI frameworks/tools. • Strong understanding of machine learning, deep learning, LLMs, prompt engineering, and techniques like RAG and fine-tuning. • Experience with data processing, embeddings, vector databases, APIs, and building scalable AI driven applications. • Good communication skills, ability to work on multiple projects, and eagerness to learn and adapt to evolving AI technologies. 

Staff Engineer - AI:

Location : India, Remote

Job Description

Egnyte is seeking an experienced Staff Software Engineer to join our Engineering department. The Engineering department builds large distributed components and services that run Egnyte's Cloud Platform. Our code serves billions of requests per day with sub-second latency in a fault-tolerant environment. We process and analyze millions of files and events daily. Some of the responsibilities for this department include Egnyte's Cloud File System, Content Classification, Content Lifecycle Management, User Behavior Analysis, Object Store, Metadata Stores, Search Systems, Recommendations Systems, Synchronization, and intelligent caching of multi-petabyte datasets. We are looking for candidates with a shared passion for building large-scale distributed systems and a keen sense for tackling complexities that come with scaling through multiple orders of magnitude.

In this role, you will (But are not limited to):

• Design and develop highly scalable and resilient cloud architecture that seamlessly integrates with on-premises systems
• Drive the team’s goals and technical direction to find and pursue technical opportunities that make Egnyte’s cloud platform more efficient
• Effectively communicate complex design and architecture details
• Understand company and industry-wide trends to help develop new technologies
• Conceptualize, develop, and implement changes that prevent key systems from becoming unreliable, under-utilized, or unsupported
• Own all aspects of critical software projects from design to implementation, QA, deployment, and monitoring

Qualifications

• BS, MS, or PhD. in Computer Science or related technical field, or equivalent practical experience
• 8-15 years of professional experience in engineering with a history of technical innovation
• Experience providing technical leadership to engineers

Bonus Qualifications (Good to Have)

• The breadth of knowledge across infrastructure domains, with the ability to reason about everything from data center machine software to database solutions to machine learning infrastructure to front-end web or mobile applications
• Demonstrated success in designing and developing large-scale, complex systems
• Expertise with multi-tenant, highly complex, cloud solutions; experience with Hybrid and/or on-premises solutions desired

About Egnyte

In a content critical age, Egnyte fuels business growth by enabling content-rich business processes, while also providing organizations with visibility and control over their content assets. Egnyte’s cloud-native content services platform leverages the industry’s leading content intelligence engine to deliver a simple, secure, and vendor-neutral foundation for managing enterprise content across business applications and storage repositories. More than 16,000 customers trust Egnyte to enhance employee productivity, automate data management, and reduce file-sharing cost and complexity. Investors include Google Ventures, Kleiner Perkins, Caufield & Byers, and Goldman Sachs. For more information, visit www.egnyte.com

Role Overview 

We are looking for an AI Engineer to design, build, and ship production AI systems, including agentic AI applications, for enterprise clients. This is a hands-on engineering role: you will write production code, build and evaluate models and agents, and work closely with architects and product teams to take solutions from prototype to scale. 

Key Responsibilities 

Design and build agentic AI systems: agent workflows, tool/function-calling, memory, and human-in-the-loop patterns. Build and productionise RAG pipelines, prompt-based applications, and LLM integrations across providers. Develop and maintain data and ML pipelines: feature engineering, model training, evaluation, and monitoring. Integrate AI systems with enterprise applications (CRMs, ERPs, ITSM tools) via APIs, events, and MCP-based tool servers. Implement guardrails, prompt-injection defences, and evaluation frameworks to keep AI systems safe and reliable in production. 

Write clean, tested, production-grade code and participate actively in code and design reviews. 

Collaborate with architects, product managers, and delivery teams to translate requirements into working AI solutions. Troubleshoot and optimise AI systems for accuracy, latency, and cost in production. 

Required Qualifications 

8–12 years of hands-on software engineering experience, with a strong, unbroken technical track record. Hands-on experience building and shipping AI/ML systems in production, not just POCs. 

Practical experience with agentic AI systems and at least one major agent framework (LangGraph, CrewAI, AutoGen, OpenAI Agents SDK, Bedrock Agents/Strands, or Semantic Kernel). 

Experience with LLM/GenAI systems: RAG pipelines, prompt engineering, structured outputs, and tool calling across providers. 

Strong Python skills (TypeScript/Node.js a plus), with production-grade testing, CI/CD, and API design practices. Working knowledge of ML fundamentals: model evaluation, feature engineering, and experimentation. Cloud-native experience on AWS and/or Azure: containers, serverless, event backbones, and vector databases. Understanding of LLM safety and reliability practices: guardrails, prompt-injection defences, and observability. 

Strong Backend Software Engineer Profile with strong Core Java expertise

2

Mandatory (Experience 1): Must have 2+ years of hands-on backend software engineering experience.

3

Mandatory (Experience 2): Must be able to design and implement moderately complex features with minimal supervision, and contribute to system design and architecture discussions.

4

Mandatory (Experience 3): Must be comfortable owning business-critical production components — maintaining connectors, handling customer escalations, security fixes, bug fixes, and building new features end-to-end.

5

Mandatory (Tech skill 1): Must have strong, current Core Java depth with solid, clear coding fundamentals — Java is the primary skill for this role. Deep hands-on core engineering strength matters more than framework knowledge.

6

Mandatory (Tech skill 2): Must have strong core backend engineering fundamentals and experience with scalable systems (connectors handle millions of events/data points daily across customers).

7

Mandatory (Tech skill 3): Must have microservices experience.

8

Mandatory (AI Fluency 1): Must have demonstrated, hands-on use of AI coding assistants (Claude, GitHub Copilot, Cursor, etc.) as a core part of the daily workflow — scaffolding, writing tests, reviewing code, and debugging.

9

Mandatory (AI Fluency 2): Must be able to write precise, effective prompts for production-quality output, decompose tasks so AI assistance is effective, and critically evaluate AI-generated code for correctness, security, and standards before merging.

10

Mandatory (Company): Must come from a product company background (B2B SaaS or B2C both acceptable).

11

Mandatory (Note1): This is a 3-month contract role. Candidate must be comfortable with the contract engagement and able to join immediately (urgent — onboarding within ~a week)

12

Mandatory (Note 2): Must be based in or near Chennai, Bangalore, or Ahmedabad (Chennai: hybrid, Tue & Thu in office)

13

Preferred (Backend): Hands-on Python experience is a plus.

14

Preferred (Database): Hands-on database / JDBC integration experience in a production environment.