Computational Biologist

We are building an advanced, AI-driven multi-agent software system designed to revolutionize task automation and code generation. This is a futuristic AI platform capable of:

✅ Real-time self-coding based on tasks  

✅ Autonomous multi-agent collaboration  

✅ AI-powered decision-making  

✅ Cross-platform compatibility (Desktop, Web, Mobile)  

We are hiring a highly skilled **AI Engineer & Full-Stack Developer** based in India, with a strong background in AI/ML, multi-agent architecture, and scalable, production-grade software development.

### Responsibilities:

- Build and maintain a multi-agent AI system (AutoGPT, BabyAGI, MetaGPT concepts)  

- Integrate large language models (GPT-4o, Claude, open-source LLMs)  

- Develop full-stack components (Backend: Python, FastAPI/Flask, Frontend: React/Next.js)  

- Work on real-time task execution pipelines  

- Build cross-platform apps using Electron or Flutter  

- Implement Redis, Vector databases, scalable APIs  

- Guide the architecture of autonomous, self-coding AI systems  

### Must-Have Skills:

- Python (advanced, AI applications)  

- AI/ML experience, including multi-agent orchestration  

- LLM integration knowledge  

- Full-stack development: React or Next.js  

- Redis, Vector Databases (e.g., Pinecone, FAISS)  

- Real-time applications (websockets, event-driven)  

- Cloud deployment (AWS, GCP)  

### Good to Have:

- Experience with code-generation AI models (Codex, GPT-4o coding abilities)  

- Microservices and secure system design  

- Knowledge of AI for workflow automation and productivity tools  

Join us to work on cutting-edge AI technology that builds the future of autonomous software.

Must of Skills/Experience 

• System Design

• Python

• TensorFlow

• Google ADK or Lang Graph

• Lang Chain , Lang Graph

• Spark

• Agentic AI Design

• ML Ops

• MCP (client and server)

• FastAPI

• Doc Factory

• RAG

• Golang

• LLMs – Gemini, Open AI

• NLP

• Dev Assistant - AI based code - generation

(Qwen or Claude or Copilot)

• CI/CD

• Good in oral and written communication,

collaboration and be a team player

Good to have skills 

• DevOps with K8

• Scripting

• Java

• REST API

• UV

• ReACT

• DocFactory

• Unix

Key Responsibilities:

·      Architectural Leadership: Design and lead the development of robust, scalable AI architectures, ensuring high performance, reliability, and security.

·      Applied Mathematics & Statistics: Apply statistical analysis, numerical computation, and mathematical modeling to derive insights from large-scale data and optimize model performance.

·      Deep Learning Development: Design, train, and deploy advanced Deep Learning (DL) models.

·      Technical Mentorship: Mentor engineering teams on best practices for AI/ML, coding standards, and architectural design.

·      Model Optimization: Optimize models for speed, efficiency, and accuracy using techniques like pruning, quantization, or GPU acceleration.

·      Strategy & Innovation: Evaluate and select appropriate AI frameworks, tools, and platforms, staying abreast of cutting-edge research and industry trends.

Qualifications:

Required:

·      Education: Master's or PhD in Computer Science, Applied Mathematics, Statistics, Physics, or a related quantitative field.

·      Experience: 10+ years of experience in software development, with at least 3-5 years in a Applied Mathematics and Deep learning.

·      AI/ML Expertise: Proven experience designing and deploying deep learning models in production using frameworks.

·      Mathematics/Statistics: Strong proficiency in linear algebra, calculus, probability, and statistical methods.

·      Programming Skills: Expert-level coding skills in Python (NumPy, Pandas, Scikit-learn) and experience with languages like Java or C++.

Key Competencies:

• Strategic mindset with deep operational awareness.
• Excellent communication and stakeholder management skills.
• Ability to simplify complex technical concepts for executive reporting.
• Strong leadership, people development, and cross-functional influencing skills.

Bias for action and a relentless focus on continuous improvement.

AuxoAI is hiring a Senior Applied Scientist to design and deploy production-grade AI agents capable of structured reasoning, planning, and decision-making.

This role focuses on building reasoning and decision systems using planning algorithms, search methods, and optimization techniques, rather than chatbot or RAG-style application development. The ideal candidate will design intelligent agent architectures that combine LLM-based reasoning with classical planning, search algorithms, and optimization techniques, operating reliably in real-world environments with constraints around latency, cost, uncertainty, and limited context windows.

You will work on advanced AI systems that power autonomous workflows, decision engines, and tool-driven agent ecosystems.

You will also work on problems where existing architectures may not be sufficient, and will be expected to experiment with new approaches that combine machine learning, graph algorithms, and classical AI techniques to build reliable, production-grade systems.

Location - Mumbai/Bangalore/Hyderabad/Gurgaon (Hybrid - 3 Days a week in Office)

Responsibilities:

• Design and architect modular AI agent frameworks incorporating skill decomposition, tool orchestration, and persistent state tracking.
• Implement planning and search algorithms such as Monte Carlo Tree Search (MCTS), beam search, A search, heuristic search, and graph-based planning approaches* to support complex decision-making tasks.
• Develop decision-making loops that balance trade-offs between exploration vs. exploitation, cost vs. accuracy, and latency vs. reasoning depth.
• Build structured memory systems including episodic memory stores, semantic memory layers, and vector-based memory with optimized retrieval strategies.
• Design tool-calling architectures with strong execution validation, retry mechanisms, and failure recovery strategies.
• Develop evaluation frameworks to measure agent performance using task success metrics, rollout simulations, and multi-sample validation approaches.
• Improve agent performance through techniques such as distillation, synthetic trajectory generation, prompt compression, and context pruning.
• Deliver production-ready agent systems that meet operational requirements around reliability, cost efficiency, throughput, and observability.

Requirements

• 3-10 years of experience building machine learning or AI systems in production environments.
• Strong experience implementing search or planning algorithms beyond basic use cases, including tree search or heuristic-based planning approaches.
• Hands-on experience with Monte Carlo Tree Search (MCTS) or related decision-making frameworks.
• Strong understanding of state-space representations, heuristic design, and decision boundary trade-offs.
• Experience building or extensively customizing agent frameworks for real-world applications.
• Hands-on experience designing tool-use or function-calling architectures under practical system constraints.
• Strong Python engineering skills with a focus on scalable and reliable system design.
• 
  

Candidates whose primary experience is limited to RAG pipelines, prompt engineering, or chatbot frameworks without deeper algorithmic or systems work may not be a fit for this role.

Nice to Have:

• Experience with reinforcement learning techniques such as policy gradients, value estimation, or reward modeling.
• Experience building multi-agent or collaborative agent systems.
• Experience designing evaluation frameworks for agent robustness and reliability.
• Experience optimizing LLM inference pipelines for latency, throughput, and cost efficiency.
• Familiarity with distributed task orchestration systems and large-scale AI workflow management.

AI based systems design and development, entire pipeline from image/ video ingest, metadata ingest, processing, encoding, transmitting.

Implementation and testing of advanced computer vision algorithms.

Dataset search, preparation, annotation, training, testing, fine tuning of vision CNN models. Multimodal AI, LLMs, hardware deployment, explainability.

Detailed analysis of results. Documentation, version control, client support, upgrades.

POSITION OVERVIEW

We are seeking an experienced Senior Data Scientist & Generative AI Specialist on a contractual basis to support a premier Germany-based chemical manufacturing enterprise. In this role, you will lead the end-to-end design, development, and deployment of production-grade GenAI applications, multi-modal LLM workflows, and advanced retrieval platforms tailored to complex industrial and enterprise data ecosystems.

Working closely with cross-functional global teams, you will build robust backend microservices, implement state- of-the-art RAG/GraphRAG architectures, and leverage cloud-native AI infrastructure (Azure, Vector DBs, Knowledge Graphs) to drive operational efficiency and data-driven innovation.

KEY RESPONSIBILITIES

• GenAI & LLM System Engineering: Design, build, and deploy production-grade multi-modal GenAI applications processing text, structured technical documentation, images, and telemetry data.
• Advanced RAG & Graph Architecture: Implement cutting-edge Retrieval-Augmented Generation (RAG) and GraphRAG pipelines using document parsing frameworks, custom embeddings, vector databases, and knowledge graphs to capture complex domain relationships.
• Scalable Backend Development: Architect high-throughput, low-latency microservice APIs using Python, FastAPI, and Flask, leveraging asynchronous programming (asyncio) and strict type validation (Pydantic) for long-running LLM processes.
• Agentic Systems & Azure Ecosystem: Build autonomous agent systems using modern frameworks (MCP, A2A) and orchestrate enterprise workflows across the Microsoft Azure AI ecosystem (Azure AI Foundry, AI Search, Document Intelligence, Databricks).
• Model Optimization & Evaluation: Execute systematic LLM fine-tuning, prompt optimization, and rigorous evaluation frameworks to assess AI output accuracy, reliability, and business impact against industrial requirements.
• Data Layer Management: Architect and maintain enterprise database layers combining SQL (PostgreSQL) for structured transactional data with specialized vector search engines and graph stores.
• Rapid Prototyping: Utilize AI-assisted development tools (Copilot, Claude Code) to accelerate delivery timelines and rapidly build functional UI prototypes for client feedback.

TECHNICAL QUALIFICATIONS

Core Development & Backend:

• Python Mastery: Deep expertise in writing clean, production-ready Python using asynchronous programming (asyncio), strict type-hinting (Pydantic), and automated testing patterns.

• Backend Microservices: Hands-on experience building microservices with FastAPI and Flask structured to handle asynchronous, long-running AI background tasks.

• Database Engineering: Strong command of PostgreSQL, relational schema design, vector indexing, and knowledge graph paradigms.

Machine Learning & AI Infrastructure:

• Model Expertise: Hands-on experience with leading multi-modal LLM architectures (OpenAI, Anthropic, Google) and domain-specific AI workflows.

• Retrieval & Parsing: Proven track record with document extraction frameworks, embedding models, vector search engines, and GraphRAG architectures.

• Cloud Infrastructure: Strong proficiency with Azure AI infrastructure (Foundry, Databricks, AI Search, Document Intelligence).

• Agentic Frameworks: Practical experience with open-source agent protocols (MCP, A2A), parameter-efficient fine-tuning (PEFT/LoRA), and model evaluation methodology.

CONTRACT & REMOTE REQUIREMENTS

• Contract Engagement: Contractual structure tailored to project milestones and deliverables.

• 100% Remote Setup: Fully equipped home office with high-speed, secure internet infrastructure.

• Timezone Overlap: Guaranteed 4-hour daily overlap with Central European Time (CET/CEST - Germany) to ensure smooth collaboration with enterprise stakeholders.

• Communication: Fluent professional English communication skills (written and spoken) for asynchronous and real-time technical coordination. 

Position Overview

We are seeking a highly skilled and experienced Senior AI/ML Developer to lead the development and integration of advanced AI solutions within our product ecosystem. This role involves close collaboration with cross-functional teams including product managers, data scientists, and engineers to build AI models that solve real-world integration challenges. The ideal candidate will have a strong foundation in machine learning, deep learning, and software development, along with hands-on experience deploying AI models in production environments.

Bachelor’s degree in computer science, Data Science, Mathematics, Engineering, or a related field.

✓

8+ years of experience in designing and implementing AI/ML solutions.

✓

Demonstrated ability to integrate AI models into production software.

✓

Excellent analytical thinking, communication, and problem-solving abilities.

✓

Ability to work autonomously as well as in a collaborative team setup.

Skills Required

✓

Dataset Development: Strong track record of building datasets for training and/or evaluating machine learning models.

✓

LLM and NLP Experience: Hands-on experience working with LLMs, RAG architecture, Natural Language Processing (NLP), or applying Machine Learning to solve real-world problems.

✓

Experience with LLM fine-tuning, prompt engineering, vector databases (e.g., Pinecone, FAISS) is highly desirable.

✓

Test Harness Automation for LLM Agents

✓

Familiarity with agent frameworks (e.g., Semantic Kernel, AutoGen, Lang Chain, etc.).

✓

Proficiency in Python and libraries like Pandas, NumPy, Scikit-learn, etc. containerization (Docker), and API frameworks (Flask, Fast API).

✓

Integration Knowledge: API development, data transformation, system integration

✓

Soft Skills: Communication, teamwork, adaptability, critical thinking

About LeadSquared

LeadSquared is a leading sales execution and marketing automation platform trusted by 2,000+ businesses globally, including healthcare, education, financial services, and real estate. Headquartered in Bengaluru with offices across the US, UK, UAE, and Southeast Asia, we empower sales teams to close faster, smarter, and at scale.

Our AI team is at the forefront of integrating cutting-edge large language model capabilities into enterprise workflows — building intelligent agents, copilots, and automation systems that redefine how businesses operate.

Role Overview

We are looking for a Senior AI Engineer with hands-on experience building LLM-powered agents and agentic AI systems. You will design, develop, and deploy autonomous AI pipelines that solve complex, multi-step business problems — from lead qualification and follow-up automation to intelligent CRM workflows and beyond.

This role is ideal for someone who is deeply excited about the frontier of AI, can move fast, and wants their work to directly impact millions of sales professionals worldwide.

Key Responsibilities

•

Design and build LLM-powered agentic systems using frameworks such as LangChain, LlamaIndex, AutoGen, or CrewAI to automate complex, multi-step workflows.

•

Develop and maintain Retrieval-Augmented Generation (RAG) pipelines with vector databases (Pinecone, Weaviate, Chroma, pgvector) for domain-specific knowledge grounding.

•

Build and integrate tool-use and function-calling capabilities into AI agents, enabling dynamic interaction with internal APIs, databases, and third-party services.

•

Implement prompt engineering strategies including chain-of-thought, few-shot prompting, and structured output parsing to ensure reliable agent behavior.

•

Design evaluation frameworks and observability pipelines (LangSmith, Helicone, custom metrics) to monitor agent performance, accuracy, and cost.

•

Collaborate with product, sales, and domain teams to translate business requirements into AI-driven solutions and features.

•

Optimize LLM inference for latency and cost using techniques like caching, model distillation, quantization, and batching.

•

Stay current with the rapidly evolving LLM ecosystem and proactively propose improvements and new approaches.

•

Contribute to internal best practices, documentation, and knowledge-sharing across the engineering org.

Required Qualifications

Experience

•

2–4 years of professional software engineering experience, with at least 1–2 years focused on LLM/AI systems.

•

Proven experience shipping LLM-based products or agentic AI systems into production environments.

Technical Skills

•

Strong proficiency in Python and familiarity with async programming patterns for AI pipelines.

•

Hands-on experience with LLM APIs: OpenAI (GPT-4o), Anthropic (Claude), Google (Gemini), or open-source models (Llama, Mistral).

•

Experience with agentic frameworks: LangChain, LangGraph, LlamaIndex, AutoGen, CrewAI, or similar.

•

Solid understanding of RAG architectures, embedding models, and semantic search.

•

Experience with vector databases and similarity search infrastructure.

•

Knowledge of REST APIs, microservices architecture, and containerization (Docker/Kubernetes).

Problem-Solving & Mindset

•

Strong ability to decompose ambiguous, open-ended problems into structured AI system designs.

•

Experience with prompt debugging, LLM evaluation, and iterative refinement workflows.

•

Ability to balance research exploration with engineering pragmatism to ship reliable systems.

Preferred Qualifications

•

Experience with multi-agent orchestration and agent memory systems (short-term and long-term).

•

Familiarity with fine-tuning or RLHF workflows for domain adaptation.

•

Background in NLP, information retrieval, or conversational AI.

•

Prior experience in B2B SaaS or CRM domain is a plus.

•

Contributions to open-source AI/ML projects or published research/blogs.

•

Experience with cloud platforms: AWS, GCP, or Azure — particularly AI/ML services

Hiring for AI Engineer

Exp: 4 - 8 yrs

Edu : BE/B.Tech/MCA

Work Location : Pune

Skill Set

Large language,Artificial Intelligence,Machine Learning

- 4–7 years of experience in software engineering/AI roles

- Strong programming skills in Python or TypeScript (Java/Go is a plus)

- Hands-on experience with LLMs, RAG pipelines, and AI frameworks

- Experience building APIs and working with distributed systems

- Familiarity with Kubernetes, Docker, and CI/CD pipelines

- Experience with cloud platforms (AWS/Azure/GCP)

Excellent communication

Strong Data Scientist / AI Engineer / Generative AI Engineer profile.

2

Mandatory (Experience 1) - Must have 3+ years of hands-on experience in Data Science, Artificial Intelligence, Machine Learning, Deep Learning, NLP, or Generative AI application development.

3

Mandatory (Experience 2) - Must have strong hands-on experience in Python programming, backend development, API development, and production-grade application support.

4

Mandatory (Experience 3) - Must have experience working with Machine Learning and Deep Learning frameworks such as PyTorch, TensorFlow, Keras, or Scikit-learn.

5

Mandatory (Experience 4) - Must have hands-on experience in NLP use cases such as text classification, sentiment analysis, entity recognition (NER), semantic search, embeddings, or document understanding.

6

Mandatory (Experience 5) - Must have experience working with Large Language Models (LLMs) such as GPT, LLaMA, Mistral, Phi, Claude, Gemini, or similar models.

7

Mandatory (Experience 6) - Must have hands-on experience building or implementing Retrieval Augmented Generation (RAG) solutions, vector search, semantic search, or knowledge-based AI applications.

8

Mandatory (Experience 7) - Must have experience with Prompt Engineering and Generative AI frameworks such as LangChain, LangGraph, AI Agents, Azure OpenAI, or similar technologies.

9

Mandatory (Experience 8) - Must have experience developing, consuming, or integrating APIs using Python frameworks such as FastAPI, Flask, or similar technologies.

10

Mandatory (CTC) - The CTC breakup offered will be 75% fixed + 25% variable, as per company policy.

11

Preferred (Experience 1) - Experience with LLMOps/MLOps tools for monitoring, evaluation, experimentation, and versioning of AI models.

12

Preferred (Experience 2) - Exposure to Azure OpenAI, Azure Kubernetes Service (AKS), Kubernetes, cloud-native AI deployments, or distributed systems.

13

Preferred (Experience 3) - Experience working with PostgreSQL, MongoDB, Redis, Kafka, or large-scale data platforms.

14

Preferred (Experience 4) - Familiarity with Docker, Kubernetes, cloud platforms, and scalable deployment architecture.

15

Preferred (Company) - Candidates from AI-first startups, product companies, SaaS organizations, fintech, or data-driven technology companies.

16

Mandatory ( Age ) - Candidate Should be Below 28 Years.

17

Mandatory ( Pedigree) - B.TECH / M.TECH from Tier 1 Colleges (IIT's, NIT's, BITS) are Considered.