{"id":2610203,"url":"https://alion.io/job/knowl-founding-engineer-ai-2","title":"Founding Engineer - AI","company":{"id":22079,"name":"Knowl","domain":"knowl.ai","url":"https://alion.io/company/knowl-ai","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"Backend","role_family":"Backend","seniority":null,"employment_type":null,"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":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"ClickHouse","optional":false},{"name":"Kubernetes","optional":false},{"name":"LLM","optional":false},{"name":"Python","optional":false},{"name":"Text-to-Speech","optional":false},{"name":"WebSockets","optional":false},{"name":"AWS","optional":true},{"name":"Azure","optional":true},{"name":"FastAPI","optional":true},{"name":"Fine-tuning","optional":true},{"name":"LoRA","optional":true},{"name":"NLP","optional":true},{"name":"PEFT","optional":true},{"name":"PostgreSQL","optional":true},{"name":"Reinforcement Learning","optional":true},{"name":"RLHF","optional":true},{"name":"TGI","optional":true},{"name":"Transformers","optional":true},{"name":"vLLM","optional":true}],"status":"live","first_seen_at":"2026-10-15T10:47:45Z","employer_posted_date":null,"last_verified_at":"2026-10-15T10:47:45Z","board_verified":false,"closed_at":null,"days_open":0,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":0},"description":"This is a Founding Engineer position, not just a title. You'll take ownership of some of our most challenging technical problems, driving them from architecture to production with real decision-making authority from day one.\nThe core responsibilities for the job include the following:\nLLM and ML Systems:\nFine-tune and optimise proprietary Small Language Models (SLMs) for Indian financial conversations.\nBuild training pipelines using domain-specific datasets.\nOptimise inference to achieve sub-200ms latency at scale.\nDevelop intent classification and end-of-utterance detection models.\nVoice and Real-Time Infrastructure:\nPush the latency limits of our real-time voice pipeline, including WebSocket audio streaming, STT, LLM, and TTS orchestration.\nBuild and maintain custom telephony infrastructure capable of handling 10,000+ concurrent AI voice calls.\nSolve complex asynchronous concurrency challenges using Python.\nDistributed Intelligence:\nArchitect data replication pipelines, scheduling systems, and observability infrastructure.\nBuild distributed systems that process millions of daily conversations.\nWork with technologies such as ClickHouse analytics, Kubernetes autoscaling, and distributed computing frameworks.\nRequirements:\nCandidates from the following backgrounds are preferred: IIT, NIT, or BITS graduates.\nEngineers from Google, Nvidia, DeepMind, or fast-scaling Indian AI startups.\nFirst-Principles Thinking:\nStrong computer science fundamentals with the ability to reason from first principles across memory management, algorithms, concurrency, and distributed systems rather than relying solely on framework documentation.\nProduction Ownership:\nProven track record of building and owning non-trivial production systems.\nStrong debugging skills with the ability to identify and resolve root causes effectively.\nFast Learner:\nPassion for AI and voice technologies.\nAbility to learn quickly and take complete ownership of problems.\nCuriosity and execution are valued more than prior experience in voice systems.\nBonus Points:\nExperience with low-latency or real-time systems such as audio/video streaming, VoIP, gaming backends, and high-frequency trading (HFT).\nHands-on experience with LLM inference optimisation, including vLLM, TGI, quantisation, and LoRA / PEFT.\nExposure to Indic language NLP or speech systems, or experience across any stage of the LLM lifecycle, including data creation, fine-tuning, and RLHF (Reinforcement Learning from Human Feedback).\nKnowl's Tech Stack: Python, FastAPI, Open Source LLMs, PostgreSQL, Azure, AWS, ClickHouse, and Kubernetes.","description_format":"text","description_chars":2592,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Artificial Intelligence","Conversational 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