AI Software Engineer
GSL Enterprise Support
/job-details/11470
AI Software Engineer
We're looking for an AI Engineer with 2+ years of hands-on experience to help design, build,and deploy AI-powered solutions that solve real business problems. You'll work closely withdata and business stakeholders to take AI initiatives from prototype to production — buildingapplications, integrating large language models (LLMs), and embedding AI capabilities intoexisting workflows and systems.
This is a hands-on role for someone who's comfortable with ambiguity, has practical experienceshipping AI features (not just experimenting with them), and wants to help shape how AI isadopted across the organization.
Duties and Responsibilities
Design, build, and deploy AI/ML-powered applications and features, from prototype throughproduction
Integrate large language models (OpenAI, Anthropic Claude, open-source models, etc.) intointernal tools and customer-facing products
Build and maintain RAG (retrieval-augmented generation) pipelines, embeddings, and vectorsearch systems
Develop and refine prompts, evaluation frameworks, and guardrails to ensure AI outputs areaccurate, safe, and reliable
Partner with business stakeholders to identify high-value use cases and translaterequirements into technical solutions
Monitor deployed AI systems for performance, drift, cost, and accuracy; iterate based on realusage data
Write clean, maintainable, well-tested code and contribute to the team's engineeringstandards and best practices
Stay current on the fast-moving AI landscape (new models, tools, and techniques) and bringrelevant innovations back to the team
Document architecture decisions, workflows, and system behavior for both technical andnon-technical audiences
Required Qualifications and Skills
Bachelor’s degree in Computer Science, Software Engineering, Data Science, AI/ML, orrelated field.
3+ years of professional experience in software engineering, machine learning engineering, orapplied AI
Strong programming skills in SQL and Python; comfortable working with APIs and backendservices
Hands-on experience working with LLMs (via API or self-hosted) - prompt engineering, fine-tuning, or RAG/CAG architecture
Experience with at least one major AI/ML framework or tool (e.g., LangChain, LangGraph,PyTorch, TensorFlow)
Experience with vector databases (e.g., Pinecone, Weaviate, pgvector) and embeddingmodels
Solid understanding of software engineering fundamentals: version control (Git), testing,CI/CD, code review practices
Experience working with cloud platforms (Azure, preferred)
Experience working with Snowflake (or a comparable cloud data warehouse) for data storage,querying, and pipeline integration
Strong communication skills — able to explain technical tradeoffs to non-technicalstakeholders
A builder's mindset: comfortable moving from ideas to working prototypes, then hardeningthem for production
Preferred Qualifications and Skills
Familiarity with Agentic AI frameworks or multi-step AI workflows
Familiarity with MLOps practices (model monitoring, versioning, deployment pipelines)
Familiarity with microservices architecture.
Familiarity with authentication and authorization of API calls
Familiarity with hosting models (Ollama, Jev, etc.) and optimizing inferences for cost andlatency.
Familiarity with Data Engineering elements such as pipelines, warehouses, data quality, andworkflows.
Familiarity with AI security topics such as prompt injection, jailbreak testing, red-teaming, andsandboxed tool execution.
If you feel you're a good fit for this role, send your CV to: info@gslsupport.com
We're looking for an AI Engineer with 2+ years of hands-on experience to help design, build,and deploy AI-powered solutions that solve real business problems. You'll work closely withdata and business stakeholders to take AI initiatives from prototype to production — buildingapplications, integrating large language models (LLMs), and embedding AI capabilities intoexisting workflows and systems.
This is a hands-on role for someone who's comfortable with ambiguity, has practical experienceshipping AI features (not just experimenting with them), and wants to help shape how AI isadopted across the organization.
Duties and Responsibilities
Design, build, and deploy AI/ML-powered applications and features, from prototype throughproduction
Integrate large language models (OpenAI, Anthropic Claude, open-source models, etc.) intointernal tools and customer-facing products
Build and maintain RAG (retrieval-augmented generation) pipelines, embeddings, and vectorsearch systems
Develop and refine prompts, evaluation frameworks, and guardrails to ensure AI outputs areaccurate, safe, and reliable
Partner with business stakeholders to identify high-value use cases and translaterequirements into technical solutions
Monitor deployed AI systems for performance, drift, cost, and accuracy; iterate based on realusage data
Write clean, maintainable, well-tested code and contribute to the team's engineeringstandards and best practices
Stay current on the fast-moving AI landscape (new models, tools, and techniques) and bringrelevant innovations back to the team
Document architecture decisions, workflows, and system behavior for both technical andnon-technical audiences
Required Qualifications and Skills
Bachelor’s degree in Computer Science, Software Engineering, Data Science, AI/ML, orrelated field.
3+ years of professional experience in software engineering, machine learning engineering, orapplied AI
Strong programming skills in SQL and Python; comfortable working with APIs and backendservices
Hands-on experience working with LLMs (via API or self-hosted) - prompt engineering, fine-tuning, or RAG/CAG architecture
Experience with at least one major AI/ML framework or tool (e.g., LangChain, LangGraph,PyTorch, TensorFlow)
Experience with vector databases (e.g., Pinecone, Weaviate, pgvector) and embeddingmodels
Solid understanding of software engineering fundamentals: version control (Git), testing,CI/CD, code review practices
Experience working with cloud platforms (Azure, preferred)
Experience working with Snowflake (or a comparable cloud data warehouse) for data storage,querying, and pipeline integration
Strong communication skills — able to explain technical tradeoffs to non-technicalstakeholders
A builder's mindset: comfortable moving from ideas to working prototypes, then hardeningthem for production
Preferred Qualifications and Skills
Familiarity with Agentic AI frameworks or multi-step AI workflows
Familiarity with MLOps practices (model monitoring, versioning, deployment pipelines)
Familiarity with microservices architecture.
Familiarity with authentication and authorization of API calls
Familiarity with hosting models (Ollama, Jev, etc.) and optimizing inferences for cost andlatency.
Familiarity with Data Engineering elements such as pipelines, warehouses, data quality, andworkflows.
Familiarity with AI security topics such as prompt injection, jailbreak testing, red-teaming, andsandboxed tool execution.
If you feel you're a good fit for this role, send your CV to: info@gslsupport.com
