AI Software Engineer

The interview process at None typically starts with a timed coding test focusing on Python and data structures, followed by a deep‑dive technical round covering AI/ML concepts, system design, and observability. A final managerial interview assesses cultural fit and communication skills, with HR handling compensation. Candidates should be ready to discuss past projects, LLM fundamentals, and demonstrate problem‑solving ability.

None promotes a collaborative, learning‑first culture where engineers are encouraged to experiment and share knowledge. Growth opportunities are abundant, with clear career ladders and mentorship programs. The company emphasizes work‑life balance through flexible hours and occasional remote days.

Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or related field; minimum 60% aggregate (or CGPA 6.5/10); 2022‑2025 batch (or recent graduates); no active backlogs at the time of joining; 2‑6 years of relevant experience in software, data, or ML engineering.

Round 1: Online coding test (DSA & Python) → Round 2: Technical interview (system design, AI/ML concepts, observability) → Round 3: Managerial interview (fit, communication, project experience) → Round 4: HR discussion (CTC, policies)

Company Overview: None is a fast‑growing technology firm that focuses on building cutting‑edge AI platforms for enterprise customers. With a presence in major Indian tech hubs such as Hyderabad and Gurgaon, the company blends deep research in large language models (LLMs) with pragmatic product engineering to deliver agentic AI solutions that automate complex business workflows. The organization prides itself on a culture of rapid experimentation, strong engineering rigor, and a commitment to responsible AI, ensuring that every product is safe, reliable, and compliant with industry standards. The firm’s portfolio includes AI‑driven assistants, intelligent document processing pipelines, and custom LLM‑based agents that integrate with ERP, CRM, and other legacy systems. By leveraging cloud‑native infrastructure on AWS, Azure, and GCP, None delivers scalable services that can handle millions of requests per day while maintaining low latency and cost efficiency. Employees enjoy exposure to the latest generative AI research, hands‑on experience with production‑grade pipelines, and opportunities to influence product direction from day one. Role Summary: As an AI Software Engineer, you will be at the heart of designing and building the next generation of agentic AI platform components. You will work closely with product managers, subject‑matter experts, and platform teams to translate business problems into robust AI solutions. Your responsibilities will span the full stack—from data ingestion and feature engineering to model orchestration, observability, and safety guardrails. The role demands a blend of strong software engineering fundamentals, deep familiarity with LLM concepts, and a passion for building reliable, production‑ready AI services. Key Responsibilities: 1. Design and implement modular agentic AI components, including agents, tools, workflows, and system integrations. 2. Build and maintain observability layers (tracing, logging, metrics) for the entire AI lifecycle to monitor quality, cost, and reliability. 3. Collaborate with cross‑functional teams to convert business requirements into data, model, and orchestration specifications. 4. Develop data pipelines, feature stores, and curated datasets for training, evaluation, grounding, and safety of LLM‑based agents. 5. Lead experimentation, benchmarking, and prompt engineering efforts; analyze results and iterate on solutions. 6. Implement safety guardrails, policy controls, and output filtering to ensure compliant operation. 7. Produce comprehensive documentation, runbooks, and best‑practice guides; mentor peers on observability‑first engineering. 8. Optimize system performance, latency, and cost trade‑offs across cloud environments. 9. Participate in code reviews, CI/CD processes, and modern DevOps practices. 10. Stay abreast of emerging technologies such as LangGraph, LangChain, and new LLM advancements, and evaluate their applicability. Tech Stack: Python, LangChain/LangGraph, OpenAI APIs, AWS/GCP/Azure services, Docker, Kubernetes, Terraform, Prometheus, Grafana, ELK stack, PostgreSQL/Redshift, Pandas, Spark, dbt, Git, CI/CD pipelines. Growth Path: Junior engineers can progress to Senior AI Engineer, then to Lead AI Engineer or AI Platform Manager, with opportunities to move into product ownership or technical architecture roles. Why Join None: You will work on high‑impact AI products that solve real business problems, gain exposure to state‑of‑the‑art LLM technologies, and grow within a supportive, innovation‑driven environment that values safety, scalability, and continuous learning.