AI Engineer I – Generative AI

Candidates typically go through a three‑stage interview process: an initial technical screening, a detailed system design and LLM‑specific interview, followed by an HR conversation. The technical rounds are moderately challenging, with emphasis on data structures, algorithms, and practical knowledge of generative AI concepts. Common questions include prompt engineering scenarios, RAG pipeline design, and model fine‑tuning strategies. Preparation tips include practicing coding problems, reviewing recent LLM research, and building a small generative AI project to showcase during the interview.

In.indeed.com fosters a collaborative and inclusive environment where employees are encouraged to experiment and innovate. The platform offers ample growth opportunities, regular knowledge sharing sessions, and a healthy work‑life balance with flexible working hours.

Bachelor’s degree in Computer Science, Engineering, or related field. Minimum 60% or equivalent CGPA. Freshers are welcome. No backlog policy; however, a strong portfolio of projects or internships in AI/ML is preferred.

Round 1: Technical interview focusing on data structures, algorithms, and basic ML concepts → Round 2: Technical + System design interview covering LLM architecture, RAG pipelines, and production considerations → Round 3: HR interview assessing cultural fit and growth potential

MyAdvice is a forward‑thinking fintech startup that empowers individuals to make smarter financial decisions through AI‑driven insights and personalized advice. With a growing user base and a mission to democratize financial literacy, the company has rapidly scaled its product portfolio, integrating advanced machine learning models into its core services. The team is known for its collaborative culture, data‑centric approach, and a strong focus on delivering real‑world impact. The AI Engineer I – Generative AI role is a full‑time, remote position that invites fresh talent to join a dynamic engineering squad. As an early‑stage engineer, you will be responsible for designing, building, and deploying production‑grade generative AI solutions that power the company’s flagship products. Your work will span from prototyping LLM‑based chatbots to creating robust Retrieval‑Augmented Generation (RAG) pipelines that feed actionable insights to users. Key responsibilities include: 1. Designing and deploying generative AI applications, AI agents, and intelligent workflows. 2. Building and maintaining RAG architectures using vector databases such as Pinecone, FAISS, and Weaviate. 3. Fine‑tuning and evaluating large language models (GPT, LLaMA, Gemini, etc.). 4. Implementing prompt engineering strategies and reusable prompt frameworks. 5. Developing AI skills, system rules, guardrails, and workflow instructions. 6. Building production‑ready AI pipelines covering ingestion, preprocessing, training, evaluation, and monitoring. 7. Developing internal tools for AI experimentation and deployment. 8. Integrating AI solutions via REST APIs, microservices, and middleware. 9. Collaborating with engineering, product, and client‑success teams. 10. Implementing CI/CD, automated testing, code reviews, and version control for ML systems. Tech stack: Python, LangChain, LLM frameworks (OpenAI, HuggingFace), vector databases (Pinecone, FAISS, Weaviate), cloud platforms (AWS/GCP/Azure), MLOps tools (MLflow, DVC), CI/CD pipelines (GitHub Actions, Jenkins), and containerization (Docker, Kubernetes). Growth path: Starting as a junior engineer, you will quickly progress to a senior AI engineer, then to a lead or architect role, with opportunities to influence product strategy and mentor new hires. Why join? The role offers a competitive salary, comprehensive benefits, a remote‑first culture, flexible schedules, and a chance to work on cutting‑edge generative AI technologies that directly impact millions of users. The company values continuous learning, provides mentorship programs, and encourages experimentation in a supportive environment.