- Location
- Remote, Remote India
- Workplace
- Remote
- Type
- Internship
- Department
- IT
- Source
- RecruiterFlow
Description
Job Title: Generative AI Developer
Location: Remote
Location: Remote
About Wishup :
Wishup is India’s largest remote work platform (since 2017), connecting global businesses with top remote professionals in roles such as Virtual Assistants, Operations/Admin Managers, Executive Assistants, Project Managers, Bookkeepers, and Accountants. With a stringent 0.1% acceptance rate, each professional is upskilled and managed via our AI-based remote work tool.
Backed by marquee investors (Orios Ventures, Inflection Point Ventures, 500 Startups, and Tracxn Labs), Wishup’s leadership team includes alumni from premier institutes like IIT Madras, IIM Ahmedabad, IIT Kanpur, IIT Bombay, and DCE.
Backed by marquee investors (Orios Ventures, Inflection Point Ventures, 500 Startups, and Tracxn Labs), Wishup’s leadership team includes alumni from premier institutes like IIT Madras, IIM Ahmedabad, IIT Kanpur, IIT Bombay, and DCE.
About the Role:
We are seeking a talented and passionate Generative AI Developer to design, build, and deploy cutting-edge AI-driven applications. The ideal candidate will have a strong technical background in building end-to-end AI solutions, with demonstrable experience in popular AI agent frameworks (such as LangChain, LangGraph, etc.) and large language models (e.g., OpenAI, Anthropic). You will collaborate with cross-functional teams—including data scientists, engineers, and product managers—to deliver AI solutions that drive innovation and business impact.
Key Responsibilities
1. Design & Development
• Develop and integrate advanced generative AI solutions using popular frameworks like LangChain, LangGraph, or similar AI agent architectures.
• Implement and fine-tune large language models (LLMs) from OpenAI, Anthropic, or equivalent providers to address specific use cases.
2. Technical Leadership
• Research and recommend new AI capabilities, tools, and best practices to enhance the development process.
• Guide the organization in understanding and adopting state-of-the-art AI technologies.
3. Solution Architecture
• Collaborate with product and engineering teams to define architecture, workflows, and integration strategies for generative AI applications.
• Ensure solutions are scalable, robust, and maintainable, adhering to best security and data protection practices.
4. Model Training & Deployment
• Train, evaluate, and optimize models for performance, scalability, and cost-effectiveness.
• Deploy AI solutions to production environments (cloud or on-premise), ensuring high availability and reliability.
5. Collaboration & Communication
• Work closely with data scientists, product managers, and stakeholders to understand business requirements and translate them into technical specifications.
• Present technical concepts and project progress to internal and external stakeholders in a clear, concise manner.
6. Continuous Improvement
• Monitor and analyze production system performance, identify bottlenecks, and introduce performance optimizations.
• Stay updated with the latest advances in LLMs, generative AI, and related fields; proactively incorporate relevant innovations into the product roadmap.
1. Design & Development
• Develop and integrate advanced generative AI solutions using popular frameworks like LangChain, LangGraph, or similar AI agent architectures.
• Implement and fine-tune large language models (LLMs) from OpenAI, Anthropic, or equivalent providers to address specific use cases.
2. Technical Leadership
• Research and recommend new AI capabilities, tools, and best practices to enhance the development process.
• Guide the organization in understanding and adopting state-of-the-art AI technologies.
3. Solution Architecture
• Collaborate with product and engineering teams to define architecture, workflows, and integration strategies for generative AI applications.
• Ensure solutions are scalable, robust, and maintainable, adhering to best security and data protection practices.
4. Model Training & Deployment
• Train, evaluate, and optimize models for performance, scalability, and cost-effectiveness.
• Deploy AI solutions to production environments (cloud or on-premise), ensuring high availability and reliability.
5. Collaboration & Communication
• Work closely with data scientists, product managers, and stakeholders to understand business requirements and translate them into technical specifications.
• Present technical concepts and project progress to internal and external stakeholders in a clear, concise manner.
6. Continuous Improvement
• Monitor and analyze production system performance, identify bottlenecks, and introduce performance optimizations.
• Stay updated with the latest advances in LLMs, generative AI, and related fields; proactively incorporate relevant innovations into the product roadmap.
Required Qualifications
Educational Background
• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field—or equivalent practical experience.
• Technical Skills & Experience
• Programming Languages: Proficiency in Python (preferred) or similar languages.
• Frameworks & Tools: Demonstrable experience with AI agent frameworks like LangChain, LangGraph, or similar.
• LLM Expertise: Experience with popular LLM models (OpenAI GPT series, Anthropic Claude, etc.)—including fine-tuning and prompt engineering.
• API & Microservices: Familiarity with RESTful APIs, GraphQL, and integration patterns.
• Cloud Platforms: Hands-on experience with AWS, GCP, Azure, or other major cloud providers.
• Version Control & CI/CD: Proficiency in Git, CI/CD pipelines, and DevOps practices.
• Data Architecture: Basic understanding of databases (SQL/NoSQL)
• Soft Skills
• Strong problem-solving abilities and attention to detail.
• Excellent communication skills to collaborate effectively with cross-functional teams.
• Self-driven, with a passion for staying on top of emerging AI trends and technologies.
Educational Background
• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field—or equivalent practical experience.
• Technical Skills & Experience
• Programming Languages: Proficiency in Python (preferred) or similar languages.
• Frameworks & Tools: Demonstrable experience with AI agent frameworks like LangChain, LangGraph, or similar.
• LLM Expertise: Experience with popular LLM models (OpenAI GPT series, Anthropic Claude, etc.)—including fine-tuning and prompt engineering.
• API & Microservices: Familiarity with RESTful APIs, GraphQL, and integration patterns.
• Cloud Platforms: Hands-on experience with AWS, GCP, Azure, or other major cloud providers.
• Version Control & CI/CD: Proficiency in Git, CI/CD pipelines, and DevOps practices.
• Data Architecture: Basic understanding of databases (SQL/NoSQL)
• Soft Skills
• Strong problem-solving abilities and attention to detail.
• Excellent communication skills to collaborate effectively with cross-functional teams.
• Self-driven, with a passion for staying on top of emerging AI trends and technologies.
What We Offer
• Competitive salary and benefits package.
• Exposure to state-of-the-art AI tools and technologies.
• Opportunities for continuous learning and professional development.
• Collaborative and inclusive team culture.
• Chance to play a key role in shaping the future of AI-driven products and solutions
• Exposure to state-of-the-art AI tools and technologies.
• Opportunities for continuous learning and professional development.
• Collaborative and inclusive team culture.
• Chance to play a key role in shaping the future of AI-driven products and solutions
Skills
PythonAWSAzureGCPCI/CDSQLGitGraphQLDevOpsMicroservices