We are seeking a highly capable and proactive Senior Technical Lead – Market Surveillance to drive the successful integration, onboarding, and ongoing operational support of our market surveillance platform. This role is essential in ensuring seamless collaboration with exchanges and trading venues, coordinating data integrations, and managing the performance and change lifecycle of the surveillance solution. You will be the technical focal point between internal teams, the platform vendor, and external counterparties to ensure the platform operates reliably and meets evolving business and regulatory needs. Key Responsibilities: Platform Integration & Exchange Onboarding: ● Lead technical efforts to integrate new exchanges, venues, and data sources into the surveillance platform, coordinating across vendor, internal infrastructure, and external exchange teams. ● Facilitate onboarding of new data feeds (e.g., order, trade, drop copy, market data) including format validation, protocol mapping (e.g., FIX), normalization, and certification. ● Manage and support testing cycles with exchanges and venues, including coordination of system integration testing (SIT), user acceptance testing (UAT), and issue triage. Vendor Coordination & Change Management: ● Act as the primary technical point of contact with the market surveillance provider, ensuring the vendor delivers against SLAs and functional requirements. ● Oversee release coordination, environment management (e.g., test, UAT, prod), and feature deployments in partnership with the vendor and internal teams. ● Drive change request processes, track enhancement requests, and validate rule and configuration changes prior to production deployment. ● Ensure the SaaS platform continues to meet operational, regulatory, and security expectations. Operational Oversight: ● Monitor platform availability, data completeness, and alert performance to ensure continuous surveillance coverage. ● Support incident triage and resolution in collaboration with the SaaS vendor, DevOps, and compliance stakeholders. ● Establish and maintain dashboards, operational runbooks, and incident response protocols. ● Drive regular vendor review sessions to review KPIs, issues, and platform roadmap alignment. Cross-Functional Leadership: ● Partner with Compliance, Surveillance Operations, Legal, and IT Security to ensure surveillance capabilities align with regulatory mandates and internal controls. ● Represent technical interests in vendor governance meetings, regulatory audits, and internal control assessments. ● Translate compliance requirements into actionable technical tasks and track their delivery with vendor and internal teams. Required Qualifications: ● Bachelor’s degree in computer science, Information Systems, Engineering, or related field. ● 8+ years of experience in financial services technology, including 3+ years in a technical leadership or systems integration role. ● Strong understanding of market structure, trade lifecycle, and regulatory surveillance needs across asset classes. ● Proven experience working with third-party SaaS or managed surveillance platforms and external data providers (e.g., exchanges, brokers). ● Familiarity with integration protocols such as FIX, SFTP, REST APIs, and data transformation/validation processes. ● Excellent organizational, communication, and stakeholder management skills. Preferred Skills: ● Exposure to major market surveillance platforms (e.g., Nasdaq SMARTS, Eventus Validus, Scila, ACA, etc.). ● Familiarity with regulatory frameworks such as CAT, MAR, MiFID II, and SEC Rule 15c3-5. ● Experience managing vendor relationships in a regulated environment. ● Working knowledge of monitoring and observability tools, and cloud/SaaS operations. ● Willing to travel to UAE Job Type: Full-time Pay: ₹300,000.00 - ₹350,000.00 per month Benefits: Flexible schedule Health insurance Paid time off Provident Fund Schedule: Day shift Monday to Friday Ability to commute/relocate: Hyderabad, Telangana: Reliably commute or willing to relocate with an employer-provided relocation package (Required) Work Location: In person
We are seeking a highly capable and proactive Senior Technical Lead – Market Surveillance to drive the successful integration, onboarding, and ongoing operational support of our market surveillance platform. This role is essential in ensuring seamless collaboration with exchanges and trading venues, coordinating data integrations, and managing the performance and change lifecycle of the surveillance solution. You will be the technical focal point between internal teams, the platform vendor, and external counterparties to ensure the platform operates reliably and meets evolving business and regulatory needs. Key Responsibilities: Platform Integration & Exchange Onboarding: ● Lead technical efforts to integrate new exchanges, venues, and data sources into the surveillance platform, coordinating across vendor, internal infrastructure, and external exchange teams. ● Facilitate onboarding of new data feeds (e.g., order, trade, drop copy, market data) including format validation, protocol mapping (e.g., FIX), normalization, and certification. ● Manage and support testing cycles with exchanges and venues, including coordination of system integration testing (SIT), user acceptance testing (UAT), and issue triage. Vendor Coordination & Change Management: ● Act as the primary technical point of contact with the market surveillance provider, ensuring the vendor delivers against SLAs and functional requirements. ● Oversee release coordination, environment management (e.g., test, UAT, prod), and feature deployments in partnership with the vendor and internal teams. ● Drive change request processes, track enhancement requests, and validate rule and configuration changes prior to production deployment. ● Ensure the SaaS platform continues to meet operational, regulatory, and security expectations. Operational Oversight: ● Monitor platform availability, data completeness, and alert performance to ensure continuous surveillance coverage. ● Support incident triage and resolution in collaboration with the SaaS vendor, DevOps, and compliance stakeholders. ● Establish and maintain dashboards, operational runbooks, and incident response protocols. ● Drive regular vendor review sessions to review KPIs, issues, and platform roadmap alignment. Cross-Functional Leadership: ● Partner with Compliance, Surveillance Operations, Legal, and IT Security to ensure surveillance capabilities align with regulatory mandates and internal controls. ● Represent technical interests in vendor governance meetings, regulatory audits, and internal control assessments. ● Translate compliance requirements into actionable technical tasks and track their delivery with vendor and internal teams. Required Qualifications: ● Bachelor’s degree in computer science, Information Systems, Engineering, or related field. ● 8+ years of experience in financial services technology, including 3+ years in a technical leadership or systems integration role. ● Strong understanding of market structure, trade lifecycle, and regulatory surveillance needs across asset classes. ● Proven experience working with third-party SaaS or managed surveillance platforms and external data providers (e.g., exchanges, brokers). ● Familiarity with integration protocols such as FIX, SFTP, REST APIs, and data transformation/validation processes. ● Excellent organizational, communication, and stakeholder management skills. Preferred Skills: ● Exposure to major market surveillance platforms (e.g., Nasdaq SMARTS, Eventus Validus, Scila, ACA, etc.). ● Familiarity with regulatory frameworks such as CAT, MAR, MiFID II, and SEC Rule 15c3-5. ● Experience managing vendor relationships in a regulated environment. ● Working knowledge of monitoring and observability tools, and cloud/SaaS operations. ● Willing to travel to UAE Job Type: Full-time Pay: ₹300,000.00 - ₹350,000.00 per month Benefits: Flexible schedule Health insurance Paid time off Provident Fund Schedule: Day shift Monday to Friday Ability to commute/relocate: Hyderabad, Telangana: Reliably commute or willing to relocate with an employer-provided relocation package (Required) Work Location: In person
AI Lead – Generative & Agentic AI Systems Experience: 7–10 Years Location: Hyderabad (Hybrid) Employment Type: Full-Time About the Role: We are seeking a visionary and hands-on AI Lead to architect, build, and scale next-generation Generative and Agentic AI systems. In this role, you will drive the end-to-end lifecycle—from research and prototyping to production deployment—guiding a team of AI engineers and collaborating cross-functionally to deliver secure, scalable, and impactful AI solutions across multimodal and LLM-based ecosystems. Key Responsibilities: Architect and oversee the development of GenAI and Agentic AI workflows, including multi-agent systems and LLM-based pipelines. Guide AI engineers in best practices for RAG (Retrieval-Augmented Generation), prompt engineering, and agent design. Evaluate and implement the right technology stack: open source (Hugging Face, LangChain, LlamaIndex) vs. closed source (OpenAI, Anthropic, Mistral). Lead fine-tuning and adapter-based training (e.g., LoRA, QLoRA, PEFT). Drive inference optimization using quantization, ONNX, TensorRT, and related tools. Build and refine RAG pipelines using embedding models, vector DBs (FAISS, Qdrant), chunking strategies, and hybrid knowledge graph systems. Manage LLMOps with tools like Weights & Biases, MLflow, and ClearML, ensuring experiment reproducibility and model versioning. Design and implement evaluation frameworks for truthfulness, helpfulness, toxicity, and hallucinations. Integrate guardrails, content filtering, and data privacy best practices into GenAI systems. Lead development of multi-modal AI systems (VLMs, CLIP, LLaVA, video-text fusion models). Oversee synthetic data generation for fine-tuning in low-resource domains. Design APIs and services for Model-as-a-Service (MaaS) and AI agent orchestration. Collaborate with product, cloud, and infrastructure teams to align on deployment, GPU scaling, and cost optimization. Translate cutting-edge AI research into usable product capabilities, from prototyping to production. Mentor and grow the AI team, establishing R&D best practices and benchmarks. Stay up-to-date with emerging trends (arXiv, Papers With Code) to keep the organization ahead of the curve. Required Skills & Expertise: AI & ML Foundations: Generative AI, LLMs, Diffusion Models, Agentic AI Systems, Multi-Agent Planning, Prompt Engineering, Feedback Loops, Task Decomposition Ecosystem & Frameworks: Hugging Face, LangChain, OpenAI, Anthropic, Mistral, LLaMA, GPT, Claude, Mixtral, Falcon, etc. Fine-tuning & Inference: LoRA, QLoRA, PEFT, ONNX, TensorRT, DeepSpeed, vLLM Data & Retrieval Systems: FAISS, Qdrant, Chroma, Pinecone, Hybrid RAG + Knowledge Graphs MLOps & Evaluation: Weights & Biases, ClearML, MLflow, Evaluation metrics (truthfulness, helpfulness, hallucination) Security & Governance: Content moderation, data privacy, model alignment, ethical constraints Deployment & Ops: Cloud (AWS, GCP, Azure) with GPU scaling, Serverless LLMs, API-based inference, Docker/Kubernetes Other: Multi-modal AI (images, video, audio), API Design (Swagger/OpenAPI), Research translation and POC delivery Preferred Qualifications: 7+ years in AI/ML roles, with at least 2–3 years in a technical leadership capacity Proven experience deploying LLM-powered systems at scale Experience working with cross-functional product and infrastructure teams Contributions to open-source AI projects or published research papers (a plus) Strong communication skills to articulate complex AI concepts to diverse stakeholders Why Join Us? Work at the forefront of AI innovation with opportunities to publish, build, and scale impactful systems Lead a passionate team of engineers and researchers Shape the future of ethical, explainable, and usable AI products Ready to shape the next wave of AI? Apply now and join us on this journey! Job Types: Full-time, Permanent Pay: ₹2,500,000.00 - ₹3,500,000.00 per year Benefits: Flexible schedule Health insurance Provident Fund Supplemental Pay: Joining bonus Work Location: In person
About the Role We are seeking a visionary and hands-on AI Lead to architect, build, and scale next-generation Generative and Agentic AI systems. In this role, you will drive the end-to-end lifecycle—from research and prototyping to production deployment—guiding a team of AI engineers and collaborating cross-functionally to deliver secure, scalable, and impactful AI solutions across multimodal and LLM-based ecosystems. Key Responsibilities Architect and oversee the development of GenAI and Agentic AI workflows, including multi-agent systems and LLM-based pipelines. Guide AI engineers in best practices for RAG (Retrieval-Augmented Generation), prompt engineering, and agent design. Evaluate and implement the right technology stack: open source (Hugging Face, LangChain, LlamaIndex) vs. closed source (OpenAI, Anthropic, Mistral). Lead fine-tuning and adapter-based training (e.g., LoRA, QLoRA, PEFT). Drive inference optimization using quantization, ONNX, TensorRT, and related tools. Build and refine RAG pipelines using embedding models, vector DBs (FAISS, Qdrant), chunking strategies, and hybrid knowledge graph systems. Manage LLMOps with tools like Weights & Biases, MLflow, and ClearML, ensuring experiment reproducibility and model versioning. Design and implement evaluation frameworks for truthfulness, helpfulness, toxicity, and hallucinations. Integrate guardrails, content filtering, and data privacy best practices into GenAI systems. Lead development of multi-modal AI systems (VLMs, CLIP, LLaVA, video-text fusion models). Oversee synthetic data generation for fine-tuning in low-resource domains. Design APIs and services for Model-as-a-Service (MaaS) and AI agent orchestration. Collaborate with product, cloud, and infrastructure teams to align on deployment, GPU scaling, and cost optimization. Translate cutting-edge AI research into usable product capabilities, from prototyping to production. Mentor and grow the AI team, establishing R&D best practices and benchmarks. Stay up-to-date with emerging trends (arXiv, Papers With Code) to keep the organization ahead of the curve. Required Skills & Expertise AI & ML Foundations: Generative AI, LLMs, Diffusion Models, Agentic AI Systems, Multi-Agent Planning, Prompt Engineering, Feedback Loops, Task Decomposition Ecosystem & Frameworks: Hugging Face, LangChain, OpenAI, Anthropic, Mistral, LLaMA, GPT, Claude, Mixtral, Falcon, etc. Fine-tuning & Inference: LoRA, QLoRA, PEFT, ONNX, TensorRT, DeepSpeed, vLLM Data & Retrieval Systems: FAISS, Qdrant, Chroma, Pinecone, Hybrid RAG + Knowledge Graphs MLOps & Evaluation: Weights & Biases, ClearML, MLflow, Evaluation metrics (truthfulness, helpfulness, hallucination) Security & Governance: Content moderation, data privacy, model alignment, ethical constraints Deployment & Ops: Cloud (AWS, GCP, Azure) with GPU scaling, Serverless LLMs, API-based inference, Docker/Kubernetes Other: Multi-modal AI (images, video, audio), API Design (Swagger/OpenAPI), Research translation and POC delivery Preferred Qualifications 7+ years in AI/ML roles, with at least 2–3 years in a technical leadership capacity Proven experience deploying LLM-powered systems at scale Experience working with cross-functional product and infrastructure teams Contributions to open-source AI projects or published research papers (a plus) Strong communication skills to articulate complex AI concepts to diverse stakeholders Why Join Us? Work at the forefront of AI innovation with opportunities to publish, build, and scale impactful systems Lead a passionate team of engineers and researchers Shape the future of ethical, explainable, and usable AI products Ready to shape the next wave of AI? Apply now and join us on this journey! Job Type: Full-time Pay: ₹2,000,000.01 - ₹3,002,234.14 per year Benefits: Flexible schedule Health insurance Paid time off Provident Fund Schedule: Day shift Monday to Friday Supplemental Pay: Yearly bonus Work Location: In person
Python Developer with web development experience to join our team. The ideal candidate will have proficiency in Python, web frameworks such as Django or Flask, and front-end scripting languages like JavaScript. Additionally, knowledge of web deployment processes and basic architectural concepts will be a key asset. Also efficient, scalable, and well-structured web applications, this is the perfect role. Key Responsibilities: Python Development : Write clean, maintainable, and efficient Python code for web applications. Web Frameworks : Build dynamic web applications using Python web frameworks such as Django, Flask, and API. Front-End Scripting : Implement front-end functionalities with HTML, CSS, JavaScript, and front-end frameworks (e.g., React, Angular) to ensure a seamless user experience. Database Integration : Integrate databases (e.g., PostgreSQL, MySQL, SQLite, MongoDB) with Python-based web applications, ensuring efficient data handling and storage. API Development : Design and implement RESTful APIs and web services to integrate with other systems or front-end components. Testing & Debugging : Conduct unit tests, integration tests, and debug issues in both back-end and front-end code to ensure high-quality code delivery. Collaboration : Work closely with designers, product managers, and other developers to deliver high-quality software solutions. Documentation : Write clear documentation for the code and deployment processes. Key Skills & Qualifications: Technical Skills : o Strong proficiency in Python programming. o Hands-on experience with Django , Flask and API . o Solid understanding of front-end technologies: HTML , CSS , JavaScript (React, Angular). o Experience with version control systems. o Familiarity with database management systems (SQL or NoSQL databases). o Experience with web application deployment (Docker, etc.). o Knowledge of RESTful API design and integration. o Understanding of basic software architecture principles (e.g., MVC, microservices, monolithic structures). Bonus Skills : o Exposure to containerization technologies such as Docker . o Basic knowledge of CI/CD pipelines and automated testing frameworks. o Experience with front-end JavaScript frameworks (React or Angular). o Understanding of security practices in web development. Experience: Proven experience in Pharma related application developing, deploying and maintaining web applications. Have knowledge on Pharma equipment. 5+ years of relevant experience. Job Type: Full-time Pay: ₹600,000.00 - ₹1,200,000.00 per year Work Location: In person
Role: Head of AI Search & Growth (GEO / SEO / SEM) Function: Growth Marketing | Digital | Demand Gen Reports to: Founders (Apex Neural) Team scope: Build and lead a small pod (content, performance, marketing ops/analytics); scale as outcomes grow. Why this role exists Apex Neural is building 5060 digital ideas (products, tools, and services). We need a builder who can architect and run a unified growth engine: master the fundamentals (SEO/SEM, content, analytics) and crack the emerging frontier of GEOearning consistent inclusion and citations in AI-generated answers across major LLM/AI surfaces. Outcomes you will own (KPIs) - AI Answer Inclusion Rate (AAIR): % of target queries where Apex Neural (domain, brand, or asset) appears/cites in AI answers. - LLM Citations & Mentions: Count/quality of citations and source links from AI answers and answer cards (tracked via scripted checks/manual panels). - Non-paid pipeline: MQLs/SQLs and revenue influenced by organic (web + AI surfaces). - SEM efficiency: CAC, ROAS, MER across Google/Bing/LinkedIn/Meta; share of spend in high-intent themes. - Content authority & velocity: # of original research pieces/datasets published; authoritative backlinks; E-E-A-T signals. - Technical health: Core Web Vitals, crawl/index health, structured-data coverage, index freshness (incl. IndexNow/Bing, GSC). - Experiment throughput: # of experiments shipped/month, win rate, and time-to-learning. What youll do 1) GEO (Generative/AI Engine Optimization) - Define and execute the GEO strategy to earn inclusion in AI answers (ChatGPT, Gemini, Grok, Perplexity, Bing Copilot, Google AI Overviews). - Build an LLM Inclusion Scorecard: target prompts, competitor set, weekly tracking, screenshots, and change logs. - Create LLM-friendly assets: high-signal FAQs, How-To/Article/Guide pages, comparison tables, implementation playbooks, and concise Q&A modules aligned to real user prompts. - Structured data & entities: Maximum JSON-LD coverage (Organization, Product/Service, Article, Author/Person, FAQ, HowTo, Breadcrumb, Video, Event). Tight author/entity pages to strengthen E-E-A-T. - Original research & datasets: Publish benchmarks, studies, and open datasets (with clear licensing) that AI systems can safely cite. - Open docs & APIs: Coordinate public documentation, SDK readmes, and simple endpoints that agents can reference. - Freshness & provenance: Keep content fresh; adopt content-provenance standards (e.g., C2PA) and clear canonicalization. - Standards watch: Track/embrace new AI crawling directives, provenance signals, and submission channels as they emerge. 2) SEO (modern, technical, durable) - Full-funnel technical SEO with engineering: CWV performance, log-based crawl audits, sitemaps, hreflang (if needed), canonical hygiene, redirects, index management, IndexNow/Bing. - Content architecture for 5060 ideas: scalable pillar/cluster models, internal-link maps, programmatic pages when warranted. - Authority building: Digital PR, expert co-authorship, guest posts, and partnerships for high-quality citations. 3) SEM / Paid Growth - Own Google/Bing/LinkedIn/Meta: account structure, SKAG/intent clusters, negatives, audiences, RSAs, sitelinks, retargeting, and budget pacing. - Landing pages & CRO: Fast experiments on messaging, forms, social proof, and pricing; VWO/Optimizely/Equivalents for A/B tests. 4) Social & Content Engine - LinkedIn-first B2B calendar (founder-led POVs, case studies, artifacts, demo reels), plus YouTube how-tos and Twitter/X threads. - Content operations: briefs, outlines, editorial QA, brand voice, compliance, and repurposing (shorts, carousels, email). 5) Analytics & Ops - GTM/Tagging discipline: GA4, GSC, Bing Webmaster, LinkedIn Insight Tag, Meta Pixel; UTM governance. - Dashboards: Weekly growth report (AAIR, LLM mentions, SEO, SEM, pipeline, experiments). - Attribution: Build pragmatic multi-touch views (first-touch intent + last-touch conversion). 6) Leadership - Hire/coach a 35 person pod (performance, content, ops/analytics), and orchestrate work across 5060 initiatives after scaling initial projects. - Drive a tight experiment cadenceproblemhypothesisMVPmeasureship learning. What success looks like (30/60/90) 30 days - Full audit (SEO tech/content, SEM, analytics, social). - Baseline AAIR and LLM citations for 50 priority prompts. - GEO Playbook v0.1 and Q3 experiment backlog. 60 days - Ship schema coverage on top 200 pages; fix CWV for critical templates. - Publish 2 original research pieces (with datasets). - Launch 1015 GEO experiments; reduce waste in SEM; stand up dashboards. 90 days - 2030% inclusion on the tracked AI prompt set (directional target; refine after baseline). - 23 repeatable content AI citation playbooks. - Clear pipeline lift from organic + AI-surface traffic. Must-have experience - 2-5 years in performance/growth marketing with deep hands-on SEO + SEM and measurable wins. - Demonstrated AI-search/GEO work: examples of appearing in AI answers (screenshots, methodology, before/after). - Strong technical SEO (CWV, log analysis, schema, indexation) and paid search (account design, testing, budgeting). - Analytics fluency: GA4, GSC, Bing Webmaster, Looker Studio; comfort with funnels, cohorts, and incrementality. - Content systems: briefing, editing, and scaling expert-led content; authority & digital PR. - Experimentation mindset: speed to learning, rigorous measurement, and documentation. Nice-to-have - Basic SQL/Python for analysis; comfort with notebooks. - Exposure to LLM tooling (embeddings, RAG-friendly docs, vector stores) and docs/API publishing. - Experience in B2B AI/tech categories; familiarity with India & global markets. - VWO/Optimizely (or equivalent), Screaming Frog, Ahrefs/Semrush, Similarweb; LinkedIn Ads.