Indore, Madhya Pradesh, India
Information Technology
Full-Time
Valuebound
Overview
Job Overview
We are seeking an agile AI Engineer with a strong focus on both AI engineering and SaaS product development in a 0-1
product environment. This role is perfect for a candidate skilled in building and iterating quickly, embracing a fail fast
approach to bring innovative AI solutions to market rapidly. You will be responsible for designing, developing, and
deploying SaaS products using advanced Large Language Models (LLMs) such as Meta, Azure OpenAI, Claude, and Mistral,
while ensuring secure, scalable, and high-performance architecture. Your ability to adapt, iterate, and deliver in fast-
paced environments is critical.
Responsibilities
Lead the design, development, and deployment of SaaS products leveraging LLMs, including platforms
like Meta, Azure OpenAI, Claude, and Mistral.
Support product lifecycle, from conceptualization to deployment, ensuring seamless integration of AI
models with business requirements and user needs.
Build secure, scalable, and efficient SaaS products that embody robust data management and comply
with security and governance standards.
Collaborate closely with product management, and other stakeholders to align AI-driven SaaS solutions
with business strategies and customer expectations.
Fine-tune AI models using custom instructions to tailor them to specific use cases and optimize
performance through techniques like quantization and model tuning.
Architect AI deployment strategies using cloud-agnostic platforms (AWS, Azure, Google Cloud), ensuring
cost optimization while maintaining performance and scalability.
Apply retrieval-augmented generation (RAG) techniques to build AI models that provide contextually
accurate and relevant outputs.
Build the integration of APIs and third-party services into the SaaS ecosystem, ensuring robust and
flexible product architecture.
Monitor product performance post-launch, iterating and improving models and infrastructure to
enhance user experience and scalability.
Stay current with AI advancements, SaaS development trends, and cloud technology to apply innovative
solutions in product development.
Qualifications
Bachelor’s degree or equivalent in Information Systems, Computer Science, or related fields.
6+ years of experience in product development, with at least 2 years focused on AI-based SaaS
products.
Demonstrated experience in leading the development of SaaS products, from ideation to deployment,
with a focus on AI-driven features.
Hands-on experience with LLMs (Meta, Azure OpenAI, Claude, Mistral) and SaaS platforms.
Proven ability to build secure, scalable, and compliant SaaS solutions, integrating AI with cloud-based
services (AWS, Azure, Google Cloud).
Strong experience with RAG model techniques and fine-tuning AI models for business-specific needs.
Proficiency in AI engineering, including machine learning algorithms, deep learning architectures (e.g.,
CNNs, RNNs, Transformers), and integrating models into SaaS environments.
Solid understanding of SaaS product lifecycle management, including customer-focused design,
product-market fit, and post-launch optimization.
Excellent communication and collaboration skills, with the ability to work cross-functionally and drive
SaaS product success.
Knowledge of cost-optimized AI deployment and cloud infrastructure, focusing on scalability and
performance.
Skills:- Artificial Intelligence (AI), Generative AI, Retrieval Augmented Generation (RAG), Large Language Models (LLM) and Python
We are seeking an agile AI Engineer with a strong focus on both AI engineering and SaaS product development in a 0-1
product environment. This role is perfect for a candidate skilled in building and iterating quickly, embracing a fail fast
approach to bring innovative AI solutions to market rapidly. You will be responsible for designing, developing, and
deploying SaaS products using advanced Large Language Models (LLMs) such as Meta, Azure OpenAI, Claude, and Mistral,
while ensuring secure, scalable, and high-performance architecture. Your ability to adapt, iterate, and deliver in fast-
paced environments is critical.
Responsibilities
Lead the design, development, and deployment of SaaS products leveraging LLMs, including platforms
like Meta, Azure OpenAI, Claude, and Mistral.
Support product lifecycle, from conceptualization to deployment, ensuring seamless integration of AI
models with business requirements and user needs.
Build secure, scalable, and efficient SaaS products that embody robust data management and comply
with security and governance standards.
Collaborate closely with product management, and other stakeholders to align AI-driven SaaS solutions
with business strategies and customer expectations.
Fine-tune AI models using custom instructions to tailor them to specific use cases and optimize
performance through techniques like quantization and model tuning.
Architect AI deployment strategies using cloud-agnostic platforms (AWS, Azure, Google Cloud), ensuring
cost optimization while maintaining performance and scalability.
Apply retrieval-augmented generation (RAG) techniques to build AI models that provide contextually
accurate and relevant outputs.
Build the integration of APIs and third-party services into the SaaS ecosystem, ensuring robust and
flexible product architecture.
Monitor product performance post-launch, iterating and improving models and infrastructure to
enhance user experience and scalability.
Stay current with AI advancements, SaaS development trends, and cloud technology to apply innovative
solutions in product development.
Qualifications
Bachelor’s degree or equivalent in Information Systems, Computer Science, or related fields.
6+ years of experience in product development, with at least 2 years focused on AI-based SaaS
products.
Demonstrated experience in leading the development of SaaS products, from ideation to deployment,
with a focus on AI-driven features.
Hands-on experience with LLMs (Meta, Azure OpenAI, Claude, Mistral) and SaaS platforms.
Proven ability to build secure, scalable, and compliant SaaS solutions, integrating AI with cloud-based
services (AWS, Azure, Google Cloud).
Strong experience with RAG model techniques and fine-tuning AI models for business-specific needs.
Proficiency in AI engineering, including machine learning algorithms, deep learning architectures (e.g.,
CNNs, RNNs, Transformers), and integrating models into SaaS environments.
Solid understanding of SaaS product lifecycle management, including customer-focused design,
product-market fit, and post-launch optimization.
Excellent communication and collaboration skills, with the ability to work cross-functionally and drive
SaaS product success.
Knowledge of cost-optimized AI deployment and cloud infrastructure, focusing on scalability and
performance.
Skills:- Artificial Intelligence (AI), Generative AI, Retrieval Augmented Generation (RAG), Large Language Models (LLM) and Python
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