Synthflow AI

Provide technical support and problem resolution for enterprise IT systems. | Experience in technical support and escalation management across multi-platform environments. | Synthflow AI is a no-code platform for deploying voice AI agents that automate phone calls across contact center operations and business process outsourcing (BPO) at scale. We help mid-market and enterprise companies manage routine calls to save teams time and resources. Our agents have already delivered measurable impact: Over 5 million hours of contact center operations saved 35% more calls answered compared to non-AI operators 45 million calls handled with a 99.9% uptime Backed by Accel, Atlantic Labs, and Singular and trusted by over 1,000 customers, our growth leads an industry shift toward sophisticated and accessible conversational AI. About the Role As a Senior Sales Engineer / Solution Consultant, you are the key technical partner to the Enterprise Account Executives, driving the technical close of our largest deals. You will combine deep product expertise in AI and telephony with persuasive business acumen to articulate the value of Synthflow's AI phone agents. Your primary mission is to technically qualify opportunities, lead the solution design, and prove the platform's transformative capabilities through compelling demonstrations and tailored Proof-of-Concepts (POCs). You are the trusted advisor who ensures prospects believe not only in the technology but also in the solution architecture required for their success. Your Responsibilities: Pre-Sales Discovery: Actively partner with the Sales team, leading technical discovery meetings to deeply understand the customer's contact center, CRM, and telephony environments and key business challenges. Technical Value Presentation: Design and deliver highly compelling, customized product demonstrations and workshops that map our platform features directly to the prospect's needs and ROI objectives. Solution Design & POCs: Design end-to-end technical architectures, generate high-quality technical documentation for proposals (RFPs/RFIs), and own the execution and success of all technical Proof-of-Concepts (POCs). Expert Consulting: Serve as the technical expert during the sales cycle, addressing integration, security, and infrastructure questions from technical and non-technical stakeholders (up to the C-suite). Product Feedback: Capture structured feedback from prospects and competitive intelligence, translating it into actionable insights for the Product and Engineering teams to influence the roadmap. Enablement: Contribute to the creation of sales enablement materials, technical white papers, and best practice guides to help scale the pre-sales function. Who You Are: Spanish fluency is mandatory for this role Experience: 5+ years of progressive experience in a technical pre-sales role (Sales Engineering, Solution Consulting) within the B2B Enterprise SaaS space. Technical Depth: Hands-on experience architecting solutions involving APIs, complex system integrations (CRMs, Contact Center platforms), and workflow automation tools. Domain Focus: Strong familiarity with telephony systems (SIP, VoIP, Twilio/Genesys/Avaya/etc.), contact center operations, and a deep understanding of AI/ML concepts and prompt engineering. Business Acumen: Highly skilled at translating complex technical capabilities into clear, quantifiable business benefits and managing technical components of large, multi-threaded deals. Communication: Exceptional presentation and written communication skills; comfortable leading discussions with senior technical architects and C-level business leaders. Founded in Berlin in 2023 by serial entrepreneurs Albert Astabatsyan, Hakob Astabatsyan, and Sassun Mirzakhan-Saky, Synthflow AI democratizes access to advanced voice AI with a no-code platform that lets enterprises easily create, deploy and scale natural-sounding, cost-effective voice agents tailored to their business needs.

Design and iterate prompts for voice AI agents, build prompt-authoring tools, run evaluations and experiments, and ensure privacy compliance. | 3+ years Python production code experience, hands-on prompt engineering, LLM API integration, evaluation mindset, and customer collaboration. | Description: • Design & iterate prompts (system, tool/function-calling, task prompts) to boost voice AI agent success, reliability, and tone. • Build co-pilots for customers to author their own prompts: meta-prompted assistants that suggest structures, lint for risks, autocomplete tool schemas, critique drafts, and generate eval cases. • Work directly with customer feedback and conversation logs to identify failure modes; translate them into prompt changes, guardrails, and data improvements. • Build eval datasets (success labels, rubrics, edge cases, regressions) and run offline/online evaluations (A/B tests, canaries) to quantify impact. • Create Python utilities/services for prompt versioning, config-as-code, rollout/rollback, and guardrails (policies, refusals, redaction). • Partner with PM/Success to define success metrics (task completion, first-pass accuracy, cost, latency) and instrument dashboards/alerts. • Own LLM integration details: function/tool schemas, output parsing/validation (pydantic), retrieval-aware prompting, and fallback strategies. • Ensure privacy & compliance (PII handling, anonymization, regional data boundaries) in datasets and logs. • Share learnings via concise docs, playbooks, and internal demos. • Run a tight feedback loop with customers, turn real conversations into better prompts and eval datasets, and ship changes that measurably improve agent outcomes. Requirements: • Python: 3+ years writing clean, tested, production code (typing, pytest, profiling); experience building small services/APIs (FastAPI preferred). • Prompt Engineering: Hands-on experience designing system/tool prompts, meta-prompting, rubric graders, and iterative prompt tuning based on real user data. • LLM Integration: Comfortable with major APIs (OpenAI/Anthropic/Google/Mistral), function/tool calling, streaming, and robust output handling. • Evaluation Mindset: Ability to define measurable success, create labeled datasets, and run methodical experiments/A/B tests. • Product Sense: Comfortable talking with customers, turning qualitative feedback into shipped improvements. • Data Hygiene: Practical experience cleaning, labeling, and balancing datasets; awareness of privacy/PII constraints. • Nice-to-haves: Experience building prompt-authoring UIs/SDKs or internal tooling for prompt versioning and governance. • Nice-to-haves: Agentic frameworks & tooling: DSpy, MCP, LangGraph, LlamaIndex, Rasa; experience with agent/tool schemas and orchestration. • Nice-to-haves: Observability & eval tooling: Langfuse, LangSmith, Braintrust; building eval harnesses and experiment dashboards. • Nice-to-haves: RAG & vector stores: Qdrant/Weaviate/Pinecone and retrieval-aware prompting. • Nice-to-haves: Experimentation workflows: A/B testing, prompt diffing/versioning. • Nice-to-haves: Infra & analytics: light SQL/log analysis, metrics & tracing, simple Grafana/OTel dashboards. • Nice-to-haves: Writing public blog posts or talks about applied LLM techniques. Benefits: