Software Development Engineer Intern Backend

ABOUT PULSEAI RESEARCH (https://pulseairesearch.com/)

PulseAI Research is an AI-powered consumer intelligence and research platform, powered by Smytten. We help brands understand real consumer behaviour through data, AI, and insights from millions of real shopper interactions. From consumer research and product testing to behavioural insights, we enable brands to make faster, data-driven decisions.

As an intern, you will be working alongside the teams building and scaling our AI-powered consumer intelligence platform and the custom enterprise apps — which means real exposure to large-scale data, AI-driven product features, and systems used by the Fortune 500 companies every day.

WHAT YOU WOULD BE WORKING ON

• Design and build highly scalable, secure and fault-tolerant backend systems powering enterprise-grade AI applications across Consumer Research and Analytics.


• Build the orchestration layer for AI and agentic workflows — connecting LLMs, analytical models, data sources, research engines and enterprise applications into reliable production systems.


• Develop high-performance APIs, microservices and asynchronous processing systems that power AI-led research, analytics, dashboards, automated insight generation and enterprise integrations.


• Build backend infrastructure for GenAI applications, including model gateways, prompt and workflow orchestration, structured outputs, RAG pipelines, embeddings, vector retrieval, caching, evaluation and AI guardrails.


•  Build AI systems that operate across structured and unstructured data — survey responses, behavioural events, transactions, documents, conversations, qualitative interviews and external intelligence sources.


• Engineer multi-tenant enterprise architecture with strong data isolation, role-based access controls, auditability, authentication, API security and privacy-by-design principles.


• Build scalable research and analytics workflow engines capable of managing long-running jobs, distributed tasks, retries, queues, scheduling and real-time status updates.


• Create production-grade integrations with LLMs and machine-learning models, while solving for latency, reliability, model fallbacks, token economics, observability and output quality.


• Build systems that make AI explainable and auditable by maintaining lineage between source data, analytical transformations, model outputs and final recommendations.


• Work closely with AI/ML engineers, data scientists, researchers, product teams and analytics experts to convert complex research and analytical methodologies into scalable software products.


• Continuously experiment with new developments across LLMs, AI agents, retrieval systems, reasoning models and data infrastructure, and translate the ones that matter into production capabilities.

YOU DON’T NEED TO BE AN EXPERT — BUT THESE SHOULDN’T BE STRANGERS

• Data structures, algorithms and computer science fundamentals


• Backend development in Python, Java, Go, Node.js or equivalent


• REST/gRPC APIs and distributed system concepts


• Understanding of environment variables, and json handling


• SQL and modern database architectures


• Caching, queues and asynchronous processing


• Cloud-native application development

YOU’LL BE HARD TO IGNORE IF YOU’VE WORKED WITH ANY OF THESE

• LM APIs and Generative AI applications


• Agentic AI frameworks and workflow orchestration


• RAG, embeddings and vector databases


• ML inference systems


• Large-scale data processing


• Kafka / event-driven architectures


• Redis / Elasticsearch / OpenSearch


• Docker / Kubernetes


• AWS / GCP / Azure


• Data warehouses


• Enterprise SaaS or multi-tenant architecture

WHAT YOU WILL TAKE AWAY

• Hands-on experience designing systems that operate at consumer-internet/enterprise scale.


• A close look at how AI and data pipelines power an enterprise solutions in production.


• Ownership of real, production-facing modules — not sandbox projects.


• Mentorship from senior engineers, with structured code reviews and design discussions.


• Exposure to how an enterprise product is built, measured, and iterated at scale.


• Cross-functional collaboration with Product, Design, Data Science, and QA.

WHO CAN APPLY

• Pre-final or final year students of B.E. / B.Tech / M.E. / M.Tech / MCA (or equivalent) graduating as per the eligible batch.


• Available for a full-time, 4-6-month internship for the entire duration. (4 months minimum to qualify for PPO consideration)


• Strong fundamentals in Data Structures, Algorithms, Operating Systems, and Databases.


• Prior internships, personal projects, or open-source contributions are a strong plus.