DDry Ground AI is hiringAI Engineer
Position Overview
We are seeking a versatile and highly skilled AI Engineer to join our fast growing Full Stack AI Solutions company. This role blends the expertise of building cutting edge AI and machine learning models with the practical know how of automation and agentic system integrations.
You will design, develop, deploy, and optimize intelligent solutions that leverage generative AI, automation platforms, and agent based systems to enhance client operations, streamline workflows, and deliver measurable results.
In addition to core AI engineering, this role values engineers who can contribute to system reliability, quality assurance, and security best practices across AI driven solutions.
This is a unique opportunity to work across a wide range of technologies, from fine tuning transformer models to building real world AI powered automation stacks. If you are passionate about pushing the boundaries of AI while creating real value through systems thinking and practical implementation, this role is for you.
Key Responsibilities
AI and ML Development
- Design, build, and deploy machine learning and generative AI models for custom use cases
- Fine tune and optimize large language models such as GPT and BERT using frameworks like Hugging Face Transformers
- Conduct ongoing research to stay ahead of advancements in AI, including LLMs and generative AI
- Develop data pipelines for preprocessing, feature engineering, and model training
- Test, validate, and monitor model performance in real world scenarios, iterating for reliability and accuracy
- Ensure robustness, reliability, and security of AI systems through testing, validation, and adherence to best practices
- Collaborate with cross functional teams to embed AI into products, platforms, and services
- Mentor junior engineers and contribute to technical leadership
Automation and Agentic Systems
- Design, implement, and maintain automation workflows using tools such as LangChain, LangGraph, LangSmith, LangFuse, n8n, ElevenLabs, and CMS integrations
- Engineer system to system integrations using APIs to enable intelligent process automation
- Apply prompt and context engineering techniques to improve the performance of conversational AI tools
- Implement prompt management and QA processes for agents and assistants
- Implement quality checks, monitoring, and guardrails for agentic systems to ensure consistent and secure performance
- Explore and deploy Microsoft Copilot Studio, PowerApps, and Power Automate solutions, preferred but not required
- Continuously evaluate emerging AI and automation tools and assess their applicability in client use cases
- Collaborate with clients and internal teams to scope, deliver, and maintain solutions aligned with business goals
Qualifications
Required
- 2 or more years of hands on experience in AI or ML development, including training and deploying models in production
- Strong programming skills in Python, with proficiency in frameworks such as TensorFlow, PyTorch, Scikit learn, and Hugging Face Transformers
- Experience working with AI tools such as LangChain, OpenAI, or Stable Diffusion
- Practical experience with automation platforms and AI agent builders
- Strong understanding of machine learning algorithms, neural networks, and NLP concepts
- Experience working with REST APIs for integrations
- Familiarity with cloud based AI and ML platforms
- Strong analytical skills and ability to translate business problems into technical AI solutions
Preferred / Nice to Have
- Experience working with agentic AI frameworks, voice automation, and prompt tuning systems
- Exposure to MLOps practices such as model versioning, CI CD, and monitoring
- Knowledge of reinforcement learning, GANs, or edge AI deployments
- Familiarity with distributed computing frameworks such as Spark or Ray
- Background in AI agency workflows or client facing solution delivery
- Strong awareness of software quality practices, including testing strategies, validation frameworks, and reliability monitoring
- Familiarity with security best practices in AI and software systems, including data protection, API security, and safe deployment of AI models
- Experience contributing to QA processes, test automation, or security reviews in production environments
Work Environment and Benefits
- Competitive salary and performance based incentives
- Remote first work environment
- Collaborative and innovation driven culture
- Opportunity to work at the forefront of AI innovation across industries
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