{"id":3084991,"url":"https://alion.io/job/interview-kickstart-software-engineer-2-applied-ai","title":"Software Engineer 2 , Applied AI","company":{"id":6203,"name":"Interview Kickstart","domain":"interviewkickstart.com","url":"https://alion.io/company/interview-kickstart","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":{"grade":"B","score":75,"open_postings":6,"ghost_share":0,"stale_share":1,"repost_share":0,"time_to_fill_p50_days":40,"computed_at":"2026-11-07T05:47:08Z"}},"role":"Backend","role_family":"Backend","seniority":"middle","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Bengaluru, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":2,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"AutoGen","optional":false},{"name":"CrewAI","optional":false},{"name":"Embeddings","optional":false},{"name":"Function Calling","optional":false},{"name":"LangChain","optional":false},{"name":"LangGraph","optional":false},{"name":"LlamaIndex","optional":false},{"name":"LLM","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false}],"status":"live","first_seen_at":"2026-10-22T10:09:16Z","employer_posted_date":"2026-10-22","last_verified_at":"2026-11-07T09:38:57Z","board_verified":true,"closed_at":null,"days_open":15,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":15},"description":"Who We Are\nInterviews can be challenging, especially at top tech companies like Google, Facebook, and Netflix. Many candidates fall short simply because they are not adequately prepared. That’s where we come in\nAt Interview Kickstart, our acclaimed courses specialize in interview preparation and helping professionals transition into high-demand tech fields such as AI, ML, and Data Science. Our programs are designed and taught by current and former hiring managers from leading tech companies.\nTo date, we have helped over27,000+ tech professionals transform their careers and land roles at top technology companies. Think of us as the “everything store” for career transitions and interview skill development.\nHow Do We Do That?\nWe take a structured and holistic approach to interview success through:\nCareer Accelerator Programs designed for top tech roles\n\nA Comprehensive end-to-end learning platform\n\nA network of 750+ instructors from leading Silicon Valley companies such as Google, Facebook, Amazon, and Netflix\n\nLive classes, mock interviews, personalized coaching, resume refinement, career strategy sessions, and referrals\n\nRole Overview\nIn this role, you will work closely with the BU heads to design and build AI-native systems powered by LLMs, AI agents, and intelligent workflows. You will rapidly prototype and deploy AI tools and products that automate workflows, enhance internal systems, and unlock new AI-driven capabilities across the organization.\nYou will play a key role in building AI agents, autonomous workflows, and LLM-powered platforms that power learning, productivity, and knowledge systems.\nThis role is ideal for someone who enjoys building quickly, experimenting with emerging AI technologies, and turning ideas into production-ready systems.\nWhat Will Excite Us?\nAt least 2 - 4 years of experience software development experience/CS degree building production-grade software systems\n\nYou are working on building Agentic AI projects or building them recently.\n\nStrong programming experience in Python\n\nHands-on experience building LLM-powered applications, AI assistants, or agent-based systems\n\nExperience working with LLM orchestration frameworks such as LangChain, LangGraph, LlamaIndex, AutoGen, CrewAI, or similar tools\n\nFamiliarity with vector databases, embeddings, and Retrieval Augmented Generation (RAG) architectures\n\nExperience integrating LLMs with external tools, APIs, and structured data sources\n\nUnderstanding of prompt engineering, tool calling, and agent orchestration\n\nExperience building and deploying AI systems from prototype to production, including considerations for reliability, latency, and cost\n\nStrong understanding of backend systems, APIs, and scalable system design\n\nA strong builder mindset with the ability to rapidly prototype and iterate on AI-driven systems\n\nInterest in applying AI to learning systems, knowledge discovery, and productivity tools\n\nWhat Will You Be Doing?\nDesign and build AI agents and autonomous workflows powered by large language models\n\nDevelop systems that combine LLMs, APIs, and external tools to automate complex workflows\n\nBuild Retrieval Augmented Generation (RAG) pipelines and knowledge retrieval systems\n\nExperiment with modern AI orchestration 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