{"id":587511,"url":"https://alion.io/job/mindtickle-ai-product-engineer","title":"AI Product Engineer","company":{"id":8575,"name":"Mindtickle","domain":"mindtickle.com","url":"https://alion.io/company/mindtickle","size_band":"201-500","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Lever","truth_index":{"grade":"B","score":81,"open_postings":21,"ghost_share":0.238,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":105,"computed_at":"2026-10-28T05:59:10Z"}},"role":"Backend","role_family":"Backend","seniority":"middle","employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Pune, India","Bengaluru, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":3,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agentic Workflows","optional":false},{"name":"AI Agents","optional":false},{"name":"Django","optional":false},{"name":"FastAPI","optional":false},{"name":"Google BigQuery","optional":false},{"name":"LLM","optional":false},{"name":"LLM Guardrails","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"Snowflake","optional":false},{"name":"SQL","optional":false},{"name":"Jira","optional":true},{"name":"Zapier","optional":true}],"status":"live","first_seen_at":"2026-09-09T08:59:48Z","employer_posted_date":"2026-09-09","last_verified_at":"2026-10-29T03:51:16Z","board_verified":true,"closed_at":null,"days_open":49,"trust":{"level":"ok","repost_count":0,"flags":["company_stale"],"days_open":48},"description":"Role Overview\nWe are transitioning our organization to an AI-first operational model. We are seeking an AI Product Engineer to architect and build the company’s central intelligence engine.\nIn this role, you will be the primary builder of automated intelligence systems -tools that not only retrieve insights but actively trigger workflows, and synthesize strategic intel across our entire business landscape.\nRole Profile\nThis is a high-impact, hands-on engineering role requiring a convergence of three distinct skill sets:\nSoftware Engineering (50%): Building scalable middleware, API integrations, and production-grade applications that connect our data stack to business tools (CRM, Marketing Automation, Support/Ticketing).\n\nAI Engineering (30%): Implementing Agentic workflows, RAG architectures, and LLMs to process unstructured data at scale.\n\nData Analytics (20%): Leveraging SQL and B2B SaaS metrics to ensure all automation is grounded in accurate, governed data.\n\nKey Responsibilities\n1. Building the \"Enterprise Brain\" (Architecture & Integration)\nDevelop a unified intelligence layer that ingests signals from disparate sources (Product Telemetry, CRM, Call Transcripts, Marketing inputs) and processes them into actionable outputs.\n\nBuild robust integrations/webhooks to push AI-generated insights directly into workflow tools (e.g., pushing \"Churn Risk\" alerts into Salesforce\n\n2. AI Logic & Agent Implementation\nArchitect \"Agentic\" workflows where LLMs are granted permission to perform tasks\n\nImplement advanced RAG to ground AI outputs in company documentation, historical data, and strategic context.\n\nEnsure rigorous evaluation and guardrails for non-deterministic models to prevent \"hallucinations\" in critical business workflows.\n\n3. Data Engineering & Governance\nCollaborate with Analytics Engineers to ensure the underlying data pipelines support real-time or near-real-time AI applications.\n\nMaintain security and privacy standards, ensuring that AI agents respect data access permissions across different departments.\n\nQualifications\nMinimum Qualifications:\nEducation: Bachelor’s degree in Computer Science, Engineering, or equivalent practical experience.\n\nSoftware Engineering: 3+ years of experience in Python development, with strong proficiency in API development (FastAPI/Django) and building integrations between SaaS platforms.\n\nAI/ML Application: Proven experience building applications using LLM APIs and orchestration frameworks, Experience with \"Agent\" concepts.\n\nData Proficiency: Strong SQL skills and familiarity with cloud data warehouses (Snowflake/BigQuery).\n\nPreferred Qualifications:\nBusiness Systems Knowledge: Experience working with APIs for major B2B tools (Salesforce, HubSpot, Zendesk, Jira, Marketo).\n\nWorkflow Automation: Experience with tools like Airflow, Zapier/Make (advanced usage), or custom workflow engines.\n\nB2B Domain Expertise: Understanding of the interplay between Sales, Product, and Customer Success.\n\nCompetencies\nThe \"Builder\" Mindset: You are comfortable taking a high-level strategic requirement from leadership (e.g., \"We need to automate lead qualification\") and independently architecting and coding the solution.\n\nSystemic Thinking: You understand how a change in product data schema impacts the downstream marketing automation flow.\n\nAdaptability: You can switch contexts rapidly-from debugging a SQL query for Strategy to refining a prompt for Customer Support 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