About the Role We are seeking a Agentic AI Developer with 35 years of total software/AI experience and proven hands-on work in Agentic AI . The ideal candidate has built LLM-powered agents using frameworks like LangChain, AutoGen, CrewAI, or Semantic Kernel, and can design, deploy, and optimize autonomous AI systems for real-world business use cases. Key Responsibilities Architect, build, and deploy LLM-driven agents that can plan, reason, and execute multi-step workflows. Work with agent orchestration frameworks (LangChain, AutoGen, CrewAI, Semantic Kernel, Haystack, etc.). Develop and maintain tools, APIs, and connectors for extending agent capabilities. Implement RAG pipelines with vector databases (Pinecone, Weaviate, FAISS, Chroma, etc.). Optimize prompts, workflows, and decision-making for accuracy, cost, and reliability . Collaborate with product and engineering teams to design use-casespecific agents (e.g., copilots, data analysts, support agents). Ensure monitoring, security, and ethical compliance of deployed agents. Stay ahead of emerging trends in multi-agent systems and autonomous AI research . Required Skills 35 years of professional experience in AI/ML, software engineering, or backend development . Demonstrated hands-on experience in building agentic AI solutions (not just chatbots). Proficiency in Python (TypeScript/JavaScript is a plus). Direct experience with LLM APIs (OpenAI, Anthropic, Hugging Face, Cohere, etc.). Strong knowledge of vector databases and embeddings . Experience integrating APIs, external tools, and enterprise data sources into agents. Solid understanding of prompt engineering and workflow optimization . Strong problem-solving, debugging, and system design skills. Nice to Have Experience with multi-agent systems (agents collaborating on tasks). Prior contributions to open-source agentic AI projects . Cloud deployment knowledge ( AWS/GCP/Azure ) and MLOps practices. Background in reinforcement learning or agent evaluation . Familiarity with AI safety, monitoring, and guardrails . What We Offer Work on cutting-edge AI agent projects with direct real-world impact. Collaborative environment with strong emphasis on innovation & experimentation . Competitive salary and growth opportunities. Opportunity to specialize in one of the fastest-growing areas of AI . Show more Show less
**We are currently hiring for a senior-level position and are looking for immediate joiners only. If you are interested, please send your updated resume to [HIDDEN TEXT] along with details of your CTC, ECTC and notice period. Also please provide a brief of your experience on Predictive Analytics and Machine learning, including the total number of years of hands-on experience in these areas. ** About the Role We are looking for a visionary Senior Data Scientist who excels in predictive analytics and machine learning. You will lead the design, development, deployment, and optimization of data-driven products that drive high business impactsuch as forecasting the price/value of stocks, commodities, or consumer goods (e.g., apparel, retail). This role is for someone who has successfully taken machine learning models from concept to production, iteratively improved them based on user feedback and real-world performance, and thrives on delivering measurable results. Key Responsibilities End-to-End Product Ownership: Lead the development of predictive models from exploration and prototype to full-scale production deployment. Forecasting & Prediction: Build robust time-series and regression models to predict prices/values of financial assets, oil, apparel, and other commodities. Model Optimization: Continuously monitor and fine-tune models for accuracy, performance, and scalability using real-time data feedback. ML Ops & Deployment: Collaborate with engineering to ensure successful deployment and monitoring of models in production environments. Stakeholder Collaboration: Translate business problems into analytical frameworks, working closely with product, strategy, and business teams. Data Strategy: Define and manage pipelines and feature stores using structured and unstructured data sources. Mentorship: Guide and mentor junior data scientists and analysts in best practices and advanced modeling techniques. Required Qualifications 8+ years of experience in data science, with a strong background in predictive analytics and machine learning. Proven experience building and scaling ML models in production environments (not just notebooks or PoCs). Deep expertise in Python, SQL, and ML libraries (e.g., scikit-learn, XGBoost, LightGBM, TensorFlow/PyTorch). Strong knowledge of time-series forecasting, regression techniques, and feature engineering. Experience in domains such as finance, commodities, retail pricing, or demand prediction is highly preferred. Experience working with cloud platforms (AWS, GCP, or Azure) and tools like Airflow, Docker, and MLflow. Ability to define success metrics, conduct A/B tests, and iterate based on measurable KPIs. Excellent communication and storytelling skills with both technical and non-technical stakeholders. Preferred Experience with LLMs, deep learning, or hybrid modeling approaches. Familiarity with data privacy, compliance, and governance in production systems. Publications or thought leadership in applied machine learning or forecasting. Why Join Us Work on high-impact projects with massive data volumes. Shape predictive products that directly influence strategic business outcomes. Join a collaborative, data-first culture with real ownership and innovation. Show more Show less
** Interested candidates: please send your resumes with your salary expectations at [HIDDEN TEXT] ** About the Role Youll ship features across multiple stacks while using AI coding assistants (Cursor/Copilot/ChatGPT/Claude) to scaffold code, write tests, refactor, and debugthen verify and harden the output. Syntax can be generated; you focus on problem-solving, design, and correctness. What you will you Build/extend APIs & small UIs in PHP/Python/TypeScript (e.g., Laravel/FastAPI/Express/Next.js) Work with SQL (MySQL/Postgres) , write migrations, optimize queries; add basic caching (Redis) Use AI tools daily for boilerplate/tests/docs; maintain clean Git history and PRs Add unit/integration tests , set up simple CI, containerize with Docker Follow basic security & privacy practices (secrets, PII, validation, rate limits) Must Have Skills Comfortable in at least one of: PHP, Python, or TypeScript/JavaScript Understanding of HTTP/REST, JSON, SQL, Git, Linux basics Hands-on use of AI coding tools (share examples: prompts, before/after, lessons learned) Ability to read unfamiliar code and write small, safe changes with tests Clear written communication; curiosity and bias to ship Nice to Have React/Next.js or simple UI skills; Tailwind/shadcn Basics of LLMs (prompting, embeddings/RAG), LangChain/LlamaIndex Docker, GitHub Actions, AWS/GCP fundamentals; observability basics Show more Show less