Junior Developer-Python

Hiring for Junior AI Engineer

Exp : 4 - 6 yrs

Edu : BE/B.Tech/MCA

Work Location : Pune WFO

Skills :

- Min 3 years strong programming experience in Python is a MUST

- Min 2 years hands-on experience in AI with LLMs, RAG pipelines, and AI frameworks

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

Experience: 0–1 Year / Freshers

Location: Remote

Employment Type: Full-Time

About the Role

We are looking for a Junior Software Engineer – AI/ML with hands-on academic, internship, or personal project experience in Core AI/ML.

Key Areas We’re Looking For

• Core AI/ML
• Trading / Finance
• CCTV / Video Analytics
• Face Recognition
• OMR / OCR

Required Skills

• Python and basic Machine Learning concepts
• Experience with AI/ML projects
• Knowledge of OpenCV, Scikit-learn, PyTorch, or TensorFlow
• Basic understanding of model training, evaluation, and data preprocessing
• Git/GitHub

Candidate Profile

• Freshers or candidates with 0–1 year experience
• Practical AI/ML projects preferred
• Should be able to clearly explain their project, model/algorithm, dataset, and individual contribution

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

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

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

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

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

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

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

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

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

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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

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

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

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

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

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Experience with vector databases and similarity search infrastructure.

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

Problem-Solving & Mindset

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

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

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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).

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

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Background in NLP, information retrieval, or conversational AI.

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

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

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

We are a San Francisco-based AI infrastructure company working with leading frontier AI labs to build post-training data and evaluation infrastructure for foundation models. We are hiring a Python Developer to create high-quality datasets, reinforcement learning environments, and benchmarking pipelines used to improve and evaluate state-of-the-art LLMs. This is a remote role with flexible working hours.

Responsibilities

* Create and curate datasets for LLM post-training (SFT, RLHF, RL, preference optimization).

* Build and maintain RL environments for agent evaluation.

* Develop Python tooling for dataset generation, validation, and transformation.

* Evaluate models on custom benchmarks and testing pipelines.

* Collaborate with research and engineering teams to deliver client-specific post-training datasets.

* Work with terminal-first development workflows and cloud infrastructure.

Required Skills

* Strong Python programming skills.

* Understanding of LLM fundamentals and post-training concepts (SFT, RLHF, RL).

* Experience working with structured data (JSON, CSV, YAML).

* Git, Linux/Unix command line, and solid software engineering fundamentals.

Good to Have

Experience with RAG, agentic AI systems, Hugging Face Transformers, LoRA/PEFT, LangChain or LlamaIndex, vector databases (FAISS, Qdrant, Milvus, Pinecone, Weaviate, ChromaDB), Docker, AWS/GCP, FastAPI/Flask, Bash, CLI tooling, model evaluation frameworks, benchmarking, and AI infrastructure.

Compensation

Base Salary: USD $1,250/month

Equity: ESOP/Equity package included.

Performance Bonuses: Up to USD $4,000/month (in addition to base salary).

Location

Remote (Worldwide)

Work Hours

Flexible, remote-first, asynchronous work environment.

How to Apply

Apply here: https://tally.so/r/wLReJG

Please complete the application form and submit the required details. Only shortlisted candidates will be contacted.

Click "Apply Now" in https://gosuperedtech.com/career/ai-system-engineer to apply

Role Overview

We are looking for a Junior AI System Engineer who is eager to build a career in AI systems, automation, backend workflows, cloud infrastructure, and intelligent product operations.

This role offers an opportunity to work closely with experienced engineers, product teams, and AI specialists on real AI-powered systems that support learners, educators, schools, and internal business operations.

At GoSuper EdTech, our cloud infrastructure is built on Google Cloud Platform — GCP. You will get hands-on exposure to GCP-based systems, backend services, AI integrations, deployment workflows, monitoring, cloud storage, databases, and automation pipelines.

You will help design, integrate, test, monitor, and maintain AI-enabled systems using modern tools such as AI APIs, LLMs, automation workflows, backend services, databases, GCP services, cloud deployment tools, and monitoring systems.

This role is ideal if you are curious about AI, comfortable with technical problem-solving, and interested in building reliable systems that connect software, data, cloud infrastructure, automation, and intelligent workflows.

What You’ll Do

• Support the development and maintenance of AI-powered systems, tools, and workflows.
• Assist in integrating AI APIs, LLM platforms, automation tools, and backend services into GoSuper products.
• Work with OpenAI, Gemini, Claude, or similar AI platforms under the guidance of senior engineers.
• Support AI and backend workflows deployed on Google Cloud Platform — GCP.
• Assist with GCP-based services such as Cloud Run, Compute Engine, Cloud Functions, Cloud Storage, Firebase, Firestore, Cloud SQL, BigQuery, Pub/Sub, Cloud Logging, and Cloud Monitoring, based on project needs.
• Help build AI workflows for content generation, chatbot systems, smart recommendations, internal automation, and productivity tools.
• Support backend integrations using Node.js, Python, REST APIs, webhooks, and third-party services.
• Assist in designing and maintaining system workflows that connect databases, applications, AI models, cloud services, and business tools.
• Work with databases such as PostgreSQL, MongoDB, Firebase, Firestore, Supabase, or similar platforms.
• Help test AI outputs, validate workflows, debug issues, and improve system reliability.
• Monitor system performance, API usage, errors, logs, workflow failures, and cloud service health.
• Support deployment, configuration, and maintenance of AI-enabled product features on GCP.
• Collaborate with product managers, developers, designers, QA teams, and business teams to understand requirements and deliver working solutions.
• Participate in daily standups, sprint planning, technical discussions, and team meetings.
• Document AI workflows, system logic, API integrations, prompts, GCP configurations, deployment steps, and troubleshooting processes.
• Continuously learn and apply best practices in AI systems, backend engineering, automation, GCP cloud infrastructure, and production support.

What We’re Looking For

• 6 months to 1 year of experience in AI systems, backend development, software engineering, automation, DevOps support, cloud support, system integration, or relevant internship/project experience.
• Basic understanding of AI tools, LLMs, APIs, automation workflows, and software systems.
• Working knowledge of JavaScript, TypeScript, or Python.
• Basic backend development experience with Node.js, Express, NestJS, FastAPI, or similar frameworks.
• Basic understanding of Google Cloud Platform — GCP or willingness to learn GCP-based deployment and monitoring workflows.
• Understanding of REST APIs, webhooks, third-party integrations, and data flow between systems.
• Interest in AI APIs, prompt workflows, chatbot systems, automation tools, and intelligent product features.
• Basic understanding of databases such as PostgreSQL, MongoDB, Firebase, Firestore, Supabase, or Redis.
• Ability to debug technical issues across APIs, workflows, logs, backend services, and cloud deployments.
• Good analytical thinking and problem-solving ability.
• Ability to write clear documentation for workflows, integrations, cloud configurations, and technical processes.
• Eagerness to learn new tools, AI platforms, system design concepts, GCP services, and cloud technologies.
• Good communication skills to work with technical and non-technical teams.
• Ownership mindset and willingness to take responsibility for assigned tasks.
• Comfortable working in a fast-paced startup environment.

Nice to Have

• Familiarity with AI APIs such as OpenAI, Gemini, Claude, or similar platforms.
• Basic understanding of prompt engineering and LLM-based workflows.
• Exposure to LangChain, LlamaIndex, embeddings, vector databases, or retrieval-augmented generation.
• Basic experience with GCP services such as Cloud Run, Cloud Functions, Firebase, Firestore, Cloud Storage, Cloud SQL, BigQuery, Pub/Sub, Cloud Logging, or Cloud Monitoring.
• Exposure to Google AI tools, Vertex AI, Gemini API, or AI-related services on GCP.
• Experience with automation tools, workflow builders, webhooks, or integration platforms.
• Exposure to Docker, CI/CD pipelines, GitHub Actions, deployment workflows, or cloud-based release processes.
• Experience working with logs, monitoring tools, API testing tools, or debugging platforms.
• Familiarity with Postman, Git, GitHub, Notion, Zoho, Slack, or similar productivity tools.
• Experience building chatbots, AI assistants, internal tools, or automated workflows.
• Personal, academic, internship, or open-source projects related to AI, automation, backend systems, GCP, or cloud tools.
• Interest in SaaS, EdTech, AI-powered products, and startup environments.

What You’ll Gain

• Hands-on experience building AI-powered systems in a real startup environment.
• Practical exposure to AI APIs, LLM workflows, automation systems, backend services, and GCP cloud infrastructure.
• Mentorship from senior engineers and product leaders.
• Experience working across AI, backend engineering, databases, APIs, integrations, deployment, system monitoring, and cloud operations.
• Opportunity to contribute to real product features used by learners, educators, schools, and institutions.
• Exposure to SaaS product development, EdTech workflows, AI-driven business solutions, and GCP-based production systems.
• Learning culture that encourages experimentation, feedback, and continuous improvement.
• Opportunity to understand how AI systems are designed, deployed, monitored, scaled, and improved in production.
• Access to Cult Elite and Cult Play Pass, offering wellness and lifestyle benefits to keep you energized and inspired.

Compensation

• Competitive salary with performance-based bonuses.
• Equity ownership through ESOPs — own a piece of the company you help build.
• Flexible remote work options with occasional Bengaluru office meetups.
• Health and wellness perks, including Cult Elite membership and Cult Play Pass for employees.
• Learning and development support to help you grow in AI systems, backend engineering, automation, SaaS, and GCP cloud technologies.
• Team retreats, virtual hangouts, and a collaborative work culture.

We are looking for a AI System Engineer who is eager to build a career in AI systems, automation, backend workflows, cloud infrastructure, and intelligent product operations. Apply in https://gosuperedtech.com/career/ai-system-engineer

About the Role

We are looking for enthusiastic LLM Interns to join our team remotely for a 3-month internship. This role is ideal for students or graduates interested in AI, Natural Language Processing (NLP), and Large Language Models (LLMs). You will gain hands-on experience working with cutting-edge AI tools, prompt engineering, and model fine-tuning. While this is an unpaid internship, interns who successfully complete the program will receive a Completion Certificate and a Letter of Recommendation.

Responsibilities

• Research and experiment with LLMs, NLP techniques, and AI frameworks.
• Design, test, and optimize prompts and workflows for different use cases.
• Assist in fine-tuning or integrating LLMs for internal projects.
• Evaluate model outputs and improve accuracy, efficiency, and reliability.
• Collaborate with developers, data scientists, and product managers to implement AI-driven features.
• Document experiments, results, and best practices.

Requirements

• Strong interest in Artificial Intelligence, NLP, and Machine Learning.
• Familiarity with Python and ML libraries (e.g., TensorFlow, PyTorch, Hugging Face Transformers).
• Basic understanding of LLM concepts such as embeddings, fine-tuning, and inference.
• Knowledge of APIs (OpenAI, Anthropic, Hugging Face, etc.) is a plus.
• Good analytical and problem-solving skills.
• Ability to work independently in a remote environment.

What You’ll Gain

• Practical exposure to state-of-the-art AI tools and LLMs.
• Mentorship from AI and software professionals.
• Completion Certificate upon successful completion.
• Letter of Recommendation based on performance.
• Experience to showcase in research projects, academic work, or future AI roles.

Internship Details

• Duration: 3 months
• Location: Remote (Work from Home)
• Stipend: Unpaid
• Perks: Completion Certificate + Letter of Recommendation

We are seeking Generative AI Developers with strong Python programming and AI/ML expertise to build, deploy, and optimize LLM-powered applications. The role involves developing RAG solutions, AI agents, and enterprise GenAI applications while collaborating with cross-functional teams.

Key Responsibilities

• Develop and enhance Generative AI applications using LLMs and AI frameworks.
• Build and optimize RAG pipelines, vector search, and AI-powered workflows.
• Design effective prompts and fine-tune models using techniques such as LoRA and QLoRA.
• Develop REST APIs and integrate AI capabilities into enterprise applications.
• Deploy, monitor, and maintain AI solutions in cloud and containerized environments.
• Ensure code quality through testing, debugging, documentation, and code reviews.
• Follow Responsible AI, security, and data governance practices.

Required Technical Skills

• Strong proficiency in Python, OOP, APIs, debugging, and software development best practices.
• Good understanding of Data Structures & Algorithms, complexity analysis, and problem-solving.
• Hands-on experience with LLMs, Prompt Engineering, RAG, AI Agents, and embeddings.
• Experience with LangChain, LangGraph, LlamaIndex, Hugging Face, or similar frameworks.
• Knowledge of vector databases, semantic/hybrid search, and retrieval architectures.
• Experience with PyTorch, TensorFlow, or Keras.
• Familiarity with Docker, Git, CI/CD, and cloud platforms (Azure/AWS/GCP).
• Understanding of AI governance, data privacy, and Responsible AI principles.

Preferred Skills

• Experience with Agentic AI frameworks (CrewAI, AutoGen, Semantic Kernel).
• Exposure to Azure AI Foundry, Databricks, or enterprise AI platforms.
• Knowledge of multimodal AI applications.

Qualifications

• Bachelor's or Master's degree in Computer Science, AI, Data Science, or a related field.
• 5 years of software development experience, including AI/ML or Generative AI projects.
• Experience building and deploying production-grade AI solutions.

Assessment Focus Areas

Candidates will be evaluated on:

• Python coding and problem-solving
• Data Structures & Algorithms
• LLMs, RAG, and Agentic AI concepts
• API development and system design
• Cloud deployment and AI solution architecture

Role: AI Developer

Experience: 3–4 Years

Employment Type: Full-Time

Location: Goregaon, Mumbai

About the Role

We are looking for an experienced AI Developer with 3–4 years of software development experience and strong hands-on exposure to Generative AI, AI Agents, Copilots, and AI-powered application development.

The candidate will be responsible for building production-ready AI solutions, developing agentic workflows, modernizing legacy applications, and integrating LLM capabilities into enterprise applications.

Key Responsibilities

• Design, develop, and deploy AI Agents and agentic workflows for enterprise use cases.
• Build AI Copilots and LLM-powered applications using modern AI frameworks and APIs.
• Develop RAG-based applications using embeddings, vector databases, and enterprise data.
• Work on legacy application migration and modernization, leveraging AI-assisted development and code transformation techniques.
• Analyze legacy codebases and design strategies for AI-driven migration, refactoring, and modernization.
• Integrate LLMs with enterprise applications, APIs, databases, and third-party systems.
• Implement tool calling, function calling, multi-agent workflows, and workflow automation.
• Perform prompt engineering, context optimization, model evaluation, and AI application testing.
• Take ownership of AI solutions from POC and prototyping through production deployment.
• Collaborate with product managers, architects, and engineering teams to convert business requirements into scalable AI solutions.
• Stay updated with emerging technologies in Generative AI, Agentic AI, LLMs, and AI-assisted software development.

Required Skills

• 3–4 years of professional software development experience.
• Strong proficiency in Python and/or JavaScript/TypeScript.
• Hands-on experience developing Generative AI / LLM-based applications.
• Strong understanding of AI Agents, RAG, Prompt Engineering, LLM APIs, and embeddings.
• Experience with frameworks such as LangChain, LangGraph, Semantic Kernel, AutoGen, or equivalent.
• Experience working with REST APIs, databases, Git, and cloud environments.
• Hands-on experience with vector databases such as Pinecone, Weaviate, Chroma, FAISS, or equivalent.
• Good understanding of software architecture, debugging, testing, and deployment practices.

Good to Have

• Experience with Microsoft Copilot / Copilot Studio.
• Experience working with Claude, OpenAI, Gemini, Azure OpenAI, or open-source LLMs.
• Experience in legacy application migration, modernization, or code conversion.
• Knowledge of Azure AI / AWS / Google Cloud AI services.
• Experience with MCP, multi-agent systems, tool calling, and AI orchestration.
• Experience building enterprise-grade AI solutions with focus on security, scalability, and performance.

About the role

We are seeking an AI Engineer to build and implement AI systems for content production at scale. You'll work at the intersection of engineering and content designing prompt pipelines, integrating generative models, and building the tooling that turns source material into finished creative output. The ideal candidate is technically strong but also has taste: someone who understands story and craft, and can tell the difference between output that's technically correct and output that's actually good.

Responsibilities

• Build and iterate on prompt pipelines and multi-agent workflow components
• Design and integrate agentic workflows orchestrate multi-step, tool-using agents that plan, call models, and hand off between stages in production
• Deploy and serve open-source models set up inference endpoints, manage GPU compute, and optimize for latency and cost
• Write evals compare outputs against references, quantify quality, and feed results back into the pipeline
• Work on data pipelines: structured extraction from messy source text, localization, similarity/dedup
• Debug and maintain pipeline stages in production

What you bring:  

• (1+/3+) years of engineering experience, or a strong portfolio of shipped projects
• Solid Python fundamentals clean, working, readable code
• Hands-on experience with LLM APIs and prompt engineering (personal projects count)
• Comfort with Git, REST APIs, and working in a Linux environment
• A feel for content and narrative you can judge whether generated output is actually good, not just valid
• Curiosity and clear communication you ask good questions and don't stay stuck silently

 Preferred

• Exposure to agent/orchestration frameworks (LangGraph, LangChain, CrewAI)
• Familiarity with vector databases, embeddings, or RAG (Qdrant, pgvector)
• Hands-on work with open-source generative media models Flux, LTX, Wan, or similar
• Experience deploying open-source models for inference (vLLM, ComfyUI, Replicate/Cog, Docker + GPU)
• Experience writing evals or LLM-as-judge scoring
• Node.js and Fastapi familiarity, or experience deploying on AWS

About the role

We are seeking an AI Engineer to build and implement AI systems for content production at scale. You'll work at the intersection of engineering and content designing prompt pipelines, integrating generative models, and building the tooling that turns source material into finished creative output. The ideal candidate is technically strong but also has taste: someone who understands story and craft, and can tell the difference between output that's technically correct and output that's actually good.

Responsibilities

• Build and iterate on prompt pipelines and multi-agent workflow components
• Design and integrate agentic workflows orchestrate multi-step, tool-using agents that plan, call models, and hand off between stages in production
• Deploy and serve open-source models set up inference endpoints, manage GPU compute, and optimize for latency and cost
• Write evals compare outputs against references, quantify quality, and feed results back into the pipeline
• Work on data pipelines: structured extraction from messy source text, localization, similarity/dedup
• Debug and maintain pipeline stages in production

What you bring:  

• (1+/3+) years of engineering experience, or a strong portfolio of shipped projects
• Solid Python fundamentals clean, working, readable code
• Hands-on experience with LLM APIs and prompt engineering (personal projects count)
• Comfort with Git, REST APIs, and working in a Linux environment
• A feel for content and narrative you can judge whether generated output is actually good, not just valid
• Curiosity and clear communication you ask good questions and don't stay stuck silently

 Preferred

• Exposure to agent/orchestration frameworks (LangGraph, LangChain, CrewAI)
• Familiarity with vector databases, embeddings, or RAG (Qdrant, pgvector)
• Hands-on work with open-source generative media models Flux, LTX, Wan, or similar
• Experience deploying open-source models for inference (vLLM, ComfyUI, Replicate/Cog, Docker + GPU)
• Experience writing evals or LLM-as-judge scoring
• Node.js and Fastapi familiarity, or experience deploying on AWS