{"id":2533336,"url":"https://alion.io/job/convexicon-software-solutions-ai-engineer","title":"AI Engineer","company":{"id":4432026,"name":"Convexicon Software Solutions","domain":"convexiconindia.com","url":"https://alion.io/company/convexicon-software-solutions","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"AI/ML","role_family":"AI/ML","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":["Gurgaon, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":18500,"max_usd":51000,"period":"year","method":"role_country_seniority_unknown","sample_n":127},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Anthropic","optional":false},{"name":"Computer Vision","optional":false},{"name":"Embeddings","optional":false},{"name":"FAISS","optional":false},{"name":"Fine-tuning","optional":false},{"name":"Function Calling","optional":false},{"name":"Gemini","optional":false},{"name":"Git","optional":false},{"name":"GitHub","optional":false},{"name":"Hugging Face","optional":false},{"name":"LLM","optional":false},{"name":"Milvus","optional":false},{"name":"NLP","optional":false},{"name":"OCR","optional":false},{"name":"OpenAI","optional":false},{"name":"OpenCV","optional":false},{"name":"pgvector","optional":false},{"name":"Pinecone","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Python","optional":false},{"name":"Qdrant","optional":false},{"name":"RAG","optional":false},{"name":"Reranking","optional":false},{"name":"Semantic Search","optional":false},{"name":"Semantic Search","optional":false},{"name":"Structured Outputs","optional":false},{"name":"YOLO","optional":false},{"name":"AWS","optional":true},{"name":"Azure","optional":true},{"name":"Docker","optional":true},{"name":"GCP","optional":true},{"name":"Hybrid Search","optional":true},{"name":"LangChain","optional":true},{"name":"Linux","optional":true},{"name":"LlamaIndex","optional":true},{"name":"PostgreSQL","optional":true},{"name":"PyTorch","optional":true},{"name":"TensorFlow","optional":true},{"name":"Transformers","optional":true}],"status":"live","first_seen_at":"2026-10-14T13:32:34Z","employer_posted_date":null,"last_verified_at":"2026-10-14T13:32:34Z","board_verified":false,"closed_at":null,"days_open":0,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":0},"description":"We are looking for an AI Engineer who is especially interested in Natural Language Processing (NLP), Large Language Models (LLMs), and document intelligence, with working knowledge of Computer Vision (CV). You will work closely with our tech lead and product team to take AI capabilities from prototypes into reliable product features used by real customers. A key focus will be our Tender Management Solution (TMS): helping infrastructure consultancy and other enterprise teams understand complex tender documents, identify bid requirements, assess eligibility, and reuse their company's experience, credentials, and knowledge to prepare stronger bids. This is an opportunity to solve challenging document-understanding and information-retrieval problems, not simply build a generic chatbot.\nThe core responsibilities for the job include the following:\nNLP, LLMs, and Document Intelligence Primary Focus:\nBuild NLP/LLM pipelines that process lengthy government and enterprise tender documents, including RFPs, RFQs, eligibility criteria, technical requirements, financial clauses, deadlines, and submission checklists.\nDevelop reliable information-extraction workflows to identify and structure key tender fields, with validation, confidence indicators, and traceability to the source page or text.\nDesign and improve Retrieval-Augmented Generation (RAG) systems so users can ask questions across tender documents and company knowledge, with answers grounded in retrieved evidence and citations.\nWork on document ingestion and parsing for PDFs and scanned documents, including OCR, layout-aware extraction, tables, multi-column pages, and document chunking strategies.\nBuild semantic search, embeddings, reranking, and hybrid retrieval approaches to retrieve the most relevant tender clauses, past project credentials, CVs, and organizational documents.\nDevelop AI-assisted eligibility checking by comparing tender qualification criteria against company credentials, financial thresholds, certifications, project experience, and personnel requirements.\nHelp build the TMS Company Vault: convert unstructured company documents, project sheets, CVs, credentials, and past bid material into a searchable, reusable knowledge base.\nDevelop CV and project-experience matching workflows that map personnel qualifications, roles, years of experience, and project history to tender requirements, while highlighting gaps for human review.\nCreate structured outputs such as tender summaries, compliance matrices, risk flags, bid/no-bid inputs, and submission checklists, with clear evidence for each recommendation.\nEvaluate LLM outputs for extraction accuracy, retrieval quality, groundedness, and consistency; create test datasets and regression checks to reduce hallucinations and brittle prompt behavior.\nExperiment with prompt engineering, tool/function calling, model selection, and, where justified, fine-tuning or smaller specialized models to balance quality, latency, and cost.\nBuild safeguards for missing or conflicting information, low-confidence outputs, sensitive company data, and human approval of high-impact bid decisions.\nComputer Vision:\nContribute to computer-vision use cases across infrastructure monitoring, solid waste management, and operational automation.\nUse OpenCV and detection models such as YOLO to prototype, evaluate, or improve object detection and image/video analysis workflows.\nUnderstand image annotation, data preparation, augmentation, model evaluation, and deployment considerations for real-world camera feeds.\nCollaborate with the team to integrate model outputs into production applications and dashboards.\nRequirements:\nStrong Python programming skills and practical experience building AI/ML applications.\nGood understanding of NLP fundamentals and hands-on familiarity with LLMs, prompt engineering, and/or RAG-based applications.\nExperience with at least one major LLM API or model ecosystem, such as OpenAI, Gemini, Anthropic, or open-source Hugging Face models.\nFamiliarity with embeddings, vector databases, and semantic search; experience with tools such as FAISS, Qdrant, Pinecone, Milvus, or pgvector is useful.\nUnderstanding of document processing concepts such as OCR, text extraction, chunking, metadata, retrieval, and structured output validation.\nWorking knowledge of ML fundamentals and model evaluation; basic familiarity with computer vision concepts and tools such as OpenCV or YOLO.\nComfort working with APIs, Git/GitHub, debugging, and collaborating with software engineers to integrate AI features into applications.\nGood to have experience with LangChain, LlamaIndex, Hugging Face Transformers, or similar orchestration/model libraries.\nHands-on work with scanned PDFs, OCR engines, layout-aware document models, table extraction, or multilingual documents.\nExperience evaluating RAG systems, building test/evaluation datasets, reranking, hybrid search, or observability for LLM applications.\nExposure to PyTorch or TensorFlow, YOLO, image augmentation, or real-time video analytics.\nExperience deploying services to AWS, GCP, Azure, or Linux-based environments; familiarity with Docker is an advantage.\nInterest in enterprise workflows, bid/tender processes, infrastructure consulting, or document-heavy business operations.\nWhat We Are Looking For:\nA builder's mindset: you enjoy researching a problem, testing alternatives, and delivering a working solution.\nProduct thinking: you care about whether the AI output is accurate, explainable, and genuinely useful to an end user.\nA quality-first approach: you know that enterprise AI must handle exceptions, cite evidence, and signal uncertainty, not just produce fluent answers.\nCuriosity and ownership: you can communicate your approach, document decisions, and work closely with the tech lead and product team.","description_format":"text","description_chars":5824,"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":[],"lifecycle":[{"event":"open","at":"2026-10-14T13:32:34Z"}],"visa":[],"liveness":{"score":86,"band":"hot","label":"Hiring now","p_open":1,"p_active":0.86,"p_room":1,"age_days":0,"expected_fill_days":21,"reasons":["seen:0","win:early"],"computed_at":"2026-10-15T01:20:27Z"},"pay":null,"html_url":"https://alion.io/job/convexicon-software-solutions-ai-engineer","json_url":"https://alion.io/job/convexicon-software-solutions-ai-engineer.json","meta":{"generated_at":"2026-10-15T01:20:27Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","about":"Alion is a live layer of people, companies and AI agents: who they are, whether they are real and active right now, what they do and how to work with them, readable by people and by agents and paid per call.","catalog":"https://alion.io/catalog.json","usage":{"tier":"crawler_verified","counted_by":"address","units_charged":1,"used_today":1657,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-10-16T00:00:00Z"}},"offers":[{"id":"company.slices","title":"One company in depth, by slice","status":"live","price":{"credits":0.02,"usd":0.002,"plus_per_slice":{"credits":0.05,"usd":0.005}},"unit":"per company, plus each slice with data","note":"the employer in depth","call":{"mcp_tool":"get_company","arguments":{"id":4432026},"rest":"https://alion.io/mcp/rest/get_company?id=4432026"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fconvexicon-software-solutions-ai-engineer"},{"id":"market.stats","title":"A market slice: pay, demand and time to fill","status":"live","price":{"credits":1,"usd":0.1},"unit":"per slice","note":"pay, demand and time to fill for this role and place","call":{"mcp_tool":"market_stats"},"human":"https://alion.io/catalog?offer=market.stats&for=job%2Fconvexicon-software-solutions-ai-engineer"},{"id":"job.search","title":"Open jobs by role, technology, place, pay and visa","status":"live","price":{"credits":0.02,"usd":0.002},"unit":"per posting in a list","note":"similar open postings","call":{"mcp_tool":"search_jobs"},"human":"https://alion.io/catalog?offer=job.search&for=job%2Fconvexicon-software-solutions-ai-engineer"},{"id":"company.verify","title":"Is this company real and active right now","status":"pilot","price":null,"unit":"per company","request":{"url":"https://alion.io/catalog/request","method":"POST","body":"{\"offer\": \"company.verify\", \"for\": \"job/convexicon-software-solutions-ai-engineer\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fconvexicon-software-solutions-ai-engineer"}]}