About Solutions by Text

Solutions by Text (SBT) was founded in 2008 with the mission to deliver impactful conversational 

messaging and convenient payment partner solutions that are rich, real- time and compliant. Built 

on SMS industry best practices, the company is the only compliance- first provider of enterprise 

texting solutions in the market. More than 1400 consumer finance organizations, including leading 

brands in auto finance, banking and lending, trust SBT to ensure convenient, effective and 

compliant relationships with their millions of consumers.SBT is headquartered in Dallas, TX with 

remote teams and offices around the US and inBangalore, India. For more information, visit 

https://solutionsbytext.com/.

Game-changing Technology Built for Growth

Solutions By Text (SBT) has changed the way compliant businesses communicate and transact with 

their customers via mobile devices. Since adding its first client, SBT has quickly become the leading text 

provider to consumer finance companies and various other regulated industries. Recognized as an 

Inc 5000 fastest growing companies, SBT continues to grow and expand through the addition of great

employees who desire a growth culture.

About the role

We are hiring an AI Engineer for our Labs team a fast-moving group that prototypes emerging AI capabilities 

and takes the most promising ones to production at scale. You will operate at the intersection of research 

and engineering: turning new papers and ideas into working demos within days, then hardening them into 

reliable, production-grade systems. The ideal candidate stays on the frontier of AI, is hands-on with the full 

ML lifecycle, and thrives in ambiguity with a strong bias for action.

Job Specific Duties and Responsibilities

• End-to-end ML ownership: Drive the complete lifecycle data curation, model building, evaluation, 

deployment, monitoring, and retraining for both predictive and generative AI systems.

• Production-grade MLOps: Build scalable pipelines for training, CI/CD, model registry, A/B testing, drift 

detection, and automated retraining. Optimize inference for latency, throughput, and cost.

• LLMs and SLMs: Fine-tune and deploy open and closed models using techniques such as LoRA/QLoRA, 

PEFT, instruction tuning, and preference tuning (RLHF/DPO). Apply quantization and distillation where 

needed.

• Agentic systems: Design and productionize agentic frameworks RAG pipelines, tool/function calling,

memory, planning loops, and multi-agent orchestration with appropriate guardrails and observability.

• Quality and trust: Build evaluation frameworks (offline + online, including LLM-as-judge and red-teaming). 

Diagnose and mitigate hallucinations, bias, and drift.

• Rapid innovation: Track SOTA research, prototype quickly, and showcase work through demos and tech 

talks to internal stakeholders and leadership

AI Engineer (Python, GenAI/LLMs + ML Fundamentals)

REQUIRED QUALIFICATIONS

 3+ years of hands-on experience as an AI/ML Engineer or Applied Scientist, with proven production 

deployments including at least one LLM-based or agentic system taken to production.

 Strong Python skills and solid software engineering fundamentals (version control, testing, design patterns, 

code reviews).

 Deep Learning & NLP: Strong grasp of transformer architectures, attention, tokenization, embeddings, and 

modern NLP techniques. Hands-on with PyTorch and the Hugging Face ecosystem (Transformers, PEFT, 

TRL, Accelerate).

 Agentic & RAG stack: Working knowledge of frameworks such as LangChain / LangGraph / LlamaIndex / 

CrewAI / AutoGen, plus vector stores (Pinecone, Weaviate, Qdrant, pgvector, or FAISS) and reranking 

strategies.

 Serving & optimization: Experience with inference servers such as vLLM, TGI, or Triton, and familiarity with 

quantization (GPTQ, AWQ, GGUF).

 MLOps & infra: Hands-on with tools like MLflow, Weights & Biases, Airflow, or Kubeflow; comfortable with 

Docker, Kubernetes, GPU workloads, and at least one major cloud (AWS / Azure / GCP).

 Soft skills: High bias for action, strong communication, ownership mindset, and intellectual curiosity.

 Nice to have: Open-source contributions, multimodal model experience, on-device SLM deployment, or 

familiarity with LLM security (OWASP LLM Top 10).

EDUCATION

 B.Tech or M.Tech in Computer Science, Data Science Engineering, AI/ML Engineering, or a closely 

related quantitative discipline.

 Equivalent practical experience supported by a strong portfolio (open-source work, publications, or 

production deployments) will also be considered.

SOFT SKILLS

• Strong problem-solving and ownership mindset; comfortable operating in ambiguity.

• Clear communication of technical trade-offs and experiment results to stakeholders.

• Collaborative approach with engineering, product, and data teams.

Solutions By Text is committed to promoting the values of diversity and inclusion throughout the 

business. Whether it is through recruitment, retention, career progression or training and 

development, we are committed to improving opportunities for people regardless of their 

background or circumstances.