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Jalasoft

We provide the best software engineering solutions by investing in our people first.

AI Tech Lead

AI EngineerMachine Learning EngineerFull TimeRemoteSeniorTeam 1,001-5,000Since 2003H1B No SponsorCompany SiteLinkedIn

Location

Colombia

Posted

3 days ago

Salary

0

Seniority

Senior

Postgraduate Degree10 yrs expEnglishAWSDistributed SystemsElasticSearchRedis

Job Description

AI Tech Lead

Jalasoft

• Serving as Scrum Master and Delivery Lead for both AI teams: organizing and facilitating sprint planning, daily stand-ups, backlog grooming, and retrospectives. • Shielding both teams from day-to-day integration distractions by ensuring the junior development team receives clean task definitions, structured schemas, and clearly scoped technical requirements. • Balancing high-speed AI prototyping demands against the structured pipeline stabilization cycles required for enterprise-grade development. • Managing cross-team dependency and interface mapping to ensure smooth collaboration between the senior and junior engineering layers. • Translating strict architectural guardrails — network isolation, database connection limits, cost-containment — from the System Architects into practical workflows for the engineering teams. • Partnering with Loftware Architects to ensure teams safely leverage AWS services and data read replicas without compromising corporate security boundaries, tenant isolation, or regional compliance. • Leading technical review sessions to determine the appropriate storage strategy (Amazon MemoryDB / Redis OSS / Valkey vs. pgvector vs. OpenSearch), balancing developer needs against enterprise infrastructure standards. • Overseeing evaluation frameworks for multi-step agent workflows to ensure deterministic behavior and eliminate unhandled hallucinations. • Validating that all data ingestion flows and internal tool-calling structures adhere to type-safe validation layers, preventing malformed agent responses from breaking downstream systems or leaking PII. • Overseeing the centralized repository for system prompts, prompt caching strategies, and Amazon Bedrock configurations to ensure optimal performance, token budgeting, and corporate policy alignment. • Working with internal teams to define and enforce robust CI/CD strategies for AI agents, ensuring that changes to prompts, embeddings, or state-machine routing rules are deployed without service disruption. • Contributing to operational protocols for deployment failures mid-workflow, ensuring both teams design for idempotency to handle unexpected model degradation or pipeline failures gracefully.

Job Requirements

  • 10+ years of experience in Software Engineering and/or Technical Leadership
  • 3+ years leading AI/ML or high-throughput distributed systems teams
  • Proven track record running agile methodologies (Scrum/Kanban) across multi-tiered or split engineering teams
  • Deep hands-on architectural experience with LLMs and enterprise-scale systems
  • Experience partnering with System Architects to govern AWS infrastructure usage, security controls, and resource provisioning
  • Familiarity with agentic orchestration frameworks (LangGraph, AWS Step Functions, or equivalent) at an architectural governance level
  • Working knowledge of Amazon Bedrock APIs, Guardrails, and Knowledge Base configurations
  • Understanding of vector retrieval strategies (pgvector, Amazon OpenSearch/Elasticsearch) and in-memory data stores (Amazon MemoryDB / Redis OSS / Valkey)
  • Experience designing for idempotency and stateful rollback in distributed AI pipelines
  • Strong stakeholder management skills, with experience negotiating architectural and infrastructure decisions on behalf of engineering teams
  • Hands-on implementation experience with Vercel AI SDK, LangGraph, or LlamaIndex

Benefits

  • Remote work
  • 13 floating holiday
  • 15 vacation days per year completed
  • Good working environment

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